About Amigo

Amigo partners with healthcare organizations to deploy robust AI infrastructure that directly serves patients and providers. Our agents handle clinical workflows and patient engagement across the entire journey: pre-visit intake, care navigation, post-visit care plans, patient monitoring, and more.

We're fresh off our Series A backed by Tier 1 investors like Madrona, General Catalyst, and Optum Ventures. Our work is validated with leading academic medical institutions. Our agents have reached 3M+ patient encounters and are on track to 10x this year.

About this role

The Applied AI Engineer role at Amigo is a launchpad. You'll ship production AI agents end-to-end — writing the code, shaping product decisions, and sitting with customers as they deploy — and in doing so, you'll build the exact skill set that opens doors to the next chapter of your career at Amigo.

This role is designed to help you grow into other parts of the company. Applied AI Engineers move into one of four paths within 6–12 months:

• Applied AI: stay in the org; go deeper on agent architecture, verification frameworks, and the hardest customer problems; become a technical leader on the applied team

• Product Management: if you gravitate toward roadmap, discovery, and shaping what we build next

• Sales Engineering: if you thrive in pre-sales, technical storytelling, and closing enterprise deals

• Software Engineering: if you want to go deeper on platform, infrastructure, and core systems

You won't have to guess which fits. This role will actively help you explore each path, give you projects that stretch in those directions, and sponsor the internal transition when you're ready. People who want to stay on the applied side long-term can do that too — but this role is explicitly built so you don't have to.

What you'll do

• Implement context graphs that enable agents to select the right reasoning mode (lookup, pattern recognition, exploration) based on problem complexity

• Build and optimize agent configurations, including static personas, dynamic behaviors, and functional memory systems

• Design bounded Operational Patient Domains (OPDs) with explicit inclusions, exclusions, capabilities, and escalation rules

• Implement verification loops and simulation-based testing to validate agent performance against customer KPIs

• Write Python code for tool integrations and API orchestration within customer environments

• Build evaluation suites that gate deployments using customer-specific success metrics

• Collaborate with domain experts through structured interviews to capture reasoning patterns and clinical protocols

• Support technical power users through git-based workflows for rapid iteration

• Implement adversarial testing to systematically identify and prevent failure modes

• Ensure agents maintain audit-ready provenance with version pinning and evidence links

• Contribute to systematizing implementation patterns across different problem domains

What we're looking for

• 2+ years of production software engineering experience

• Strong Python skills including proper use of typing, and experience building highly reliable systems that interact with external APIs (schema design, retry strategies, error propagation)

• Experience with LLMs, prompt engineering, and building on AI platforms

• Ability to implement systems with strict reliability requirements

• Understanding of testing and verification methodologies

• Experience working directly with customers or stakeholders to deliver technical solutions

• Familiarity with git workflows and collaborative development

• Strong debugging and problem-solving skills for complex systems

• Ability to balance theoretical concepts with practical implementation constraints

• Clear technical communication for both engineering and non-technical audiences

Nice to have

• Experience in regulated industries (healthcare, finance, legal)

• Background with simulation, synthetic data, or evaluation frameworks

• Understanding of distributed systems and service-oriented architectures

• Experience with observability and monitoring in production environments

• Familiarity with compliance requirements (HIPAA, SOC 2, GDPR)

Benefits

Health & Wellness

• Comprehensive health, dental, and vision insurance

• Daily catered lunch and dinner

• Mental health support and wellness coaching

• Flexible wellness stipend for fitness, therapy, or personal growth

Growth & Development

• Annual learning budget for courses, books, or conferences

• Conference attendance budget for professional development

• Annual team offsite

• Academic collaboration opportunities

• Unlimited PTO

Our Core Values

1. Patients Win, We Win

   If patients aren't getting better care, we haven't earned the right to scale. Every internal decision gets pressure-tested: does this make patients' lives better? If we can't draw the line, we question why we're doing it.

2. High Standards, High Care

   We hold a high bar for the team because patients are counting on us to get this right. But high standards only work with genuine investment in each other. You can take risks, admit mistakes, and challenge ideas—not despite our standards, but because of them.

3. Thoughtful Urgency

   We move fast by default, but speed without judgment is recklessness. The discipline is knowing which decisions are reversible vs. not. In healthcare AI, the companies that win will be fast everywhere they can be and careful everywhere they must be. We build the muscle to do both.

4. Intensely Measured

   We instrument patient outcomes, provider ROI, system performance, and clinical accuracy. But data without action is surveillance. Every metric should have an owner, a threshold, and a response plan. If we're measuring something but never acting on it, we stop measuring it.

Who Builds With Us

• Low ego: Politics and territory don't interest you. The best ideas win, regardless of who has them.

• Direct: You say the hard thing, challenge ideas openly, and commit fully once decided.

• High agency: You thrive on trust rather than instruction. When you see something is broken, you fix it. You don’t file tickets and wait for someone else.

• Bar of excellence: You hold yourself to a bar most people wouldn't, and you want teammates who do the same.

• Skeptical: You push back on rules that don’t make sense and question assumptions that haven’t earned their place.

Please mention the word **READABLE** and tag RMjYwNTo0YzQwOjQwOjc1Nzk6MDplZDIyOmQzMzc6MQ== when applying to show you read the job post completely (#RMjYwNTo0YzQwOjQwOjc1Nzk6MDplZDIyOmQzMzc6MQ==). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.

We are seeking a Forward Deployed AI Engineer (FDE) to accelerate the real-world adoption of AI within our End-to-End System Test Automation. This role focuses on taking AI tools and prototypes and making them work reliably inside complex engineering environments. You will embed closely with system test engineers, automation framework/ test owners and development teams to adapt, harden and operationalize AI-driven workflows. This is a hands-on engineering role for individuals who thrive in ambiguity, enjoy working close to real users and can turn AI potential into measurable productivity gains.

Key Responsibilities:Forward Deployment of AI into Test Automation and turn AI prototypes into production-ready, repeatable solutions

Embed with system test and automation teams to:
Understand real testing workflows, constraints, and failure modes
Identify where AI can safely and effectively reduce manual effort
Adapt AI workflows to work with:
Existing automation frameworks
Real test data, schemas, and configurations

Agentic AI Implementation & TuningImplement and customize agentic AI workflows that:
Interpret requirements, schemas, or models
Assist in generating structured test assets
Tune AI behavior based on:
Real test outcomes
Failure analysis and feedback
Debug and resolve AI issues in live engineering environments

AI Tooling & Platform FeedbackWork with AI platforms (e.g., Qodo or similar) to:
Extend functionality where needed
Configure prompts, workflows, and validation layers
Evaluate emerging AI tools and frameworks in real system test contexts
Feed practical insights back to platform and leadership teams:
What works
What fails
What should scale

Enablement, Documentation & GuardrailsDocument AI usage patterns and best practices
Help define guardrails for:
Safety-critical configurations
Invalid or destructive AI-generated outputs
Enable test engineers to adopt AI confidently and responsibly

Required Qualifications2+ years of hands-on experience in software engi

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI—secure, compliant, and infrastructure-flexible deployments—H2O.ai delivers solutions that align with the highest standards of data privacy and control.

Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH.

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai’s AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users.

H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life.

For more information, visit www.h2o.ai.

The Opportunity

We are looking for a Senior AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one.

You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes.

What You

Hi Professionals,

Title: Healthcare Senior NLP / LLM Engineer (MLOps & AWS)-Onsite Role,Need Local to TXExperience: 7+ Years
Location: Houston, TX (3 days/week onsite)

Mandatory Skills:

Strong expertise in NLP, Machine Learning, and Deep LearningProficiency in Python for ML/NLP solution developmentHands-on experience with LLMs, prompt engineering, and agentic workflows (e.g., LangGraph)Solid knowledge of data preprocessing, feature engineering, and data validationStrong MLOps skills: model versioning, CI/CD, pipelines, monitoring, retrainingExperience with Docker and KubernetesProficiency in SQL for data analysis and transformationExperience with AWS (EMR, Spark, PySpark, Bedrock)Knowledge of PostgreSQL or MySQLStrong understanding of testing, error analysis, and model validation "Disclaimer: E-Solutions Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. We especially invite women, minorities, veterans, and individuals with disabilities to apply. EEO/AA/M/F/Vet/Disability.”

Healthcare Senior NLP / LLM Engineer (MLOps & AWS)-Onsite Role,Need Local to TX1AWS,NLP,health OR Healthcare,MLOps,LLMN/AC2CUnited States

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Location This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you're considering We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows. Develop and maintain automated test suites for UI, API, and data layers across multiple platforms. Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines. Build and manage test data pipelines for diverse applications and environments. Create and maintain CI/CD pipelines to support continuous testing and deployment. Identify and resolve environmental and data dependencies for comprehensive E2E testing. Lead defect triage, backlog grooming, and root cause analysis sessions. Your skills and experience Around 1 year of experience working in or supporting AIbased testing environments, or strong interest with handson exposure through projects or coursework. Working knowledge of at least one programming or scripting langua

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it's why our business strategy centers on making journalism so good that it's worth paying for.

Department Overview:

Research & Development at The New York Times explores how emerging technologies can be applied in service of journalism. We collaborate with designers, developers, reporters, photographers and editors to bring new forms of storytelling to life, from prototyping to publishing.

At The Times, technology permeates every aspect of our business, from our thought-provoking coverage of technological trends to the digital-first transformation of our own business to the changing world of our readers. The Research & Development team explores the new opportunities that emerging technologies may provide the New York Times and our commercial and strategic goals.

We are looking for a Senior Software Engineer with a background in applied AI to develop applications using Large Language Models (LLMs) in service of The Times mission and journalistic standards. We are looking for someone who is comfortable building projects autonomously and enjoys collaboration with a larger team. You are both curious about and skeptical of emerging technologies, excited to apply new tools, but aim to do so in service of solving important problems and making a difference for users. You take pride in your craft and understand the need to capture patterns and support future development. This is a temporary position.

Responsibilities:
Design and implement LLM-backed APIs - driving improvements to reach target outcomes through evaluation, grounding and fine-tu

We are hiring as many as two Senior AI Engineers who can architect and ship agentic systems, swiftly. You will be embedded in the full product lifecycle: ideation, prototyping, testing, and iteration across multiple concurrent concepts. Our first platform targets compliance automation in regulated industries, starting with affordable housing, designed to scale horizontally. When something proves out, you go deep. When it doesn't, you let it go without sentiment and move to the next. If the products you launch draw early signs of product-market fit, the resources will be assigned accordingly to seize upon the opportunity and iterate.

What You'll Do

Design and deploy multi-agent orchestration systems using frameworks like LangGraph, CrewAI, AutoGen, or equivalent, and know when to roll your own
Build full-stack prototypes fast enough to validate or kill an idea within weeks, not quarters
Own the technical architecture on 2-4 parallel concepts at any point in time
Integrate LLMs, RAG pipelines, structured data sources, and external APIs into coherent product experiences
Oversee commercialization and enterprise-upgrading to bring MVPs to full launch
Instrument everything so decisions are data-driven, not vibes-driven
Collaborate directly with the principals. There is no middle layer here

Who You Are

You have built real agentic systems, not just demo apps. You understand tool use, memory architectures, multi-agent orchestration, and evaluation at a production level. You know the difference between a clever prototype and something that actually holds up under load
You move fast and you ship. You have launched products at startups where speed was the strategy, not just a nice-to-have. Weeks, not quarters
You are full-stack by necessity, not by title. Frontend, backend, infra, pipelines. You do what needs doing and figure out the rest on the fly
You have strong opinions about what makes software work and zero patience for unnecessary complexity. You woul

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.
Location

This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you're considering

We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role
• Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows.
• Develop and maintain automated test suites for UI, API, and data layers across multiple platforms.
• Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines.
• Build and manage test data pipelines for diverse applications and environments.
• Create and maintain CI/CD pipelines to support continuous testing and deployment.
• Identify and resolve environmental and data dependencies for comprehensive E2E testing.
• Lead defect triage, backlog grooming, and root cause analysis sessions.

Your skills and experience
• Around 1 year of experience working in or supporting AIbased testing environments, or strong interest with handson exposure through projects or coursework.
• Working knowledge of at least one programming or scripting language such as Python (preferred), Java, or JavaScript.
• Basic to intermediate experience with test automation t

About the position

We are seeking an experienced LLM Engineer to join our client's newly established LLM Ops Team in their Raleigh, NC office. In this role, you will be responsible for managing the complex lifecycle of Large Language Models from development to deployment, monitoring, and continuous improvement.\n\nThis role is hybrid to the Raleigh, NC area.

Responsibilities

Fine-tune pre-trained models for specific use casesCurate and prepare datasets for trainingManage training infrastructure, resources, and computational environmentsImplement optimization techniques to improve model performanceDevelop and manage APIs for model servingScale infrastructure to handle varying demand loadsBuild and maintain the GenAI middleware/sidecar layerIntegrate LLMs with existing systems and data sourcesTrack performance metrics including latency and throughputMonitor quality metrics such as hallucination rates and accuracyOptimize costs associated with model inference and trainingCreate and maintain dashboards for real-time performance insightsCreate and maintain golden datasets for benchmark testingImplement statistical validation methods for model outputsSet up similarity matching criteria for response evaluationDevelop confidence score thresholds for production systemsDesign and implement user feedback collection systemsEstablish continuous improvement processesCreate A/B testing frameworks for model and feature evaluationConduct trace analysis to identify areas for performance optimizationImplement content moderation systemsDetect and mitigate bias in model outputsEnsure regulatory compliance in AI systemsDevelop output validation frameworksVersion and store prompts systematicallyCreate and maintain prompt templatesSet up playground environments for prompt testingAbstract prompts from application code for better maintainabilityRequirements

Experience with LLM development, fine-tuning, and deploymentStrong programming skills, particularly in PythonExperience with Kubeflo

Our company

At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.

What you will do

In this role you will:
• Lead the design and development of AI-native agentic workflows that enhance engineering productivity, observability intelligence, and end-to-end operational excellence across Teradata’s AI Platform.
• This is a Senior Individual Contributor role focused on building and deploying intelligent agents—not just integrating automation tools, but architecting AI-driven systems that reason, analyze, and act across telemetry, applications, and workflows.
• Architect and build AI agents for observability, automated root cause analysis, anomaly detection, and engineering productivity optimization.
• Design agentic workflows that integrate across telemetry pipelines, application stacks, and cloud infrastructure.
• Develop AI-driven tooling to accelerate development velocity, reduce operational toil, and improve MTTR.
• Apply LLMs, reasoning frameworks, and advanced AI patterns to automate complex debugging and system diagnostics.
• Drive AI-native development practices across apps, tooling, and platform engineering.
• Partner across engineering teams to embed intelligent automation into CI/CD, DevOps, and support workflows.
• Apply foundational AI skills to explore and implement ways AI can enhance productivity, innovation, and impact across our workforce.
• Your work will directly shape how Teradata builds, monitors, and operates its AI-powered platform. Success in this role means measurable improvements in engineer

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Design, develop, test, deploy, and support A

Location: Remote (Global)

Compensation: Competitive, dependent on experience

Type: Full-Time Contractor (2+ months, potential to extend)

Reports to: Managing Partner

About HELO Solutions

HELO Solutions is an AI consulting and product development company. We build production AI systems — agents, automation platforms, and intelligent workflows — for enterprise clients across industries including CPG, financial services, legal, and music. We also develop our own AI products. We are a small, high-output team that ships fast, operates with minimal bureaucracy, and holds a high bar for work that actually runs in production and gets used.

About the Role

We are hiring an AI Engineer who has built agents that are live in production at real companies — not demos, not prototypes that died after a pitch, not research projects. We need someone who has shipped agentic systems that enterprises depend on every day, and who understands the full lifecycle: scoping the business problem, designing the agent architecture, integrating with messy enterprise systems, building evaluation and monitoring, and keeping it running reliably.

This role sits across two priorities equally: building our internal multi-agent AI platform and delivering agent-based solutions directly to enterprise clients. You will work closely with our engineering team and the Managing Partner. You will have significant autonomy and direct impact on both the product and the business.

Responsibilities

Design, build, and deploy AI agents and multi-agent systems that solve real business problems for enterprise clients.
Architect and implement agent orchestration — coordination, handoffs, shared state, and communication between specialized agents within our multi-agent platform.
Integrate agents with enterprise systems (ERPs, CRMs, accounting platforms, APIs) to execute workflows end-to-end in production environments.
Build evaluation frameworks and production monitoring for deployed agents — loggi

Agentic AI Engineer
Enterprise Integrations, Intelligent Automation & AI Platform Delivery

Department: IT & Digital Transformation
Reports to: Sr. Director, Infrastructure & BI
Type: 6 month contract

Location: Remote - US

The Opportunity
Accuris Technologies is executing a company-wide AI transformation across 40+ initiatives spanning Finance, Sales, Marketing, Legal, RevOps, Product, HR, and Customer Experience. We have a funded roadmap, active enterprise AI licenses, and governed integrations already live across our core systems.

We are looking for an Agentic AI Engineer to lead technical delivery-building connectors, agents, and workflows that transform our CRM, ERP, HRIS, and data platforms into a unified, natural-language-driven experience. This role will bring our AI strategy to life through real, production-grade systems.

Core Responsibilities
• Design and build agentic systems that orchestrate across ERP, CRM, data warehouse, HRIS, and BI platforms
• Develop multi-step AI workflows including tool selection, data retrieval, reasoning, and response generation
• Build and extend enterprise integrations, including authentication (OAuth, SSO) and RBAC enforcement
• Deliver AI-powered business solutions such as pricing engines, SDR automation, contract workflows, and executive dashboards
• Implement governance frameworks including audit logging, data lineage, and PII protection
• Partner with business teams to translate workflows into AI-enabled solutions
• Drive adoption through reusable prompts, tools, and training for non-technical users

What We're Looking For
• 3+ years building API integrations with CRM, ERP, or HRIS systems
• Strong Python experience with LLM APIs and SDKs
• Experience with agentic architectures (tool use, function calling, multi-step workflows)
• Familiarity with AI frameworks (LangChain, MCP, or similar)
• Experience with OAuth, SSO/SAML, and enterprise authentication
• Background in data platforms, BI tools, and enterprise data gove

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

You Are:

A Forward-Deployed AI Engineer who thrives at the intersection of cutting-edge AI platforms, enterprise systems, and real-world business problems. It is a product-minded, customer-embedded engineering role where you will work directly with clients, partners, and internal product teams to design, prototype, deploy, and scale end-to-end AI solutions.

The Work:

You will work hands-on with platforms such as OpenAI, Anthropic, ServiceNow, and other enterprise systems, translating ambiguous business needs into production-grade AI workflows that deliver measurable impact.

This role requires strong engineering depth, excellent communication, comfort with ambiguity, and a builder’s mindset.

Responsibilities:

Work directly with clients and internal teams to understand business problems, shape AI use cases, and define technical solutions — often from ambiguous or evolving requirements.

Design and implement end-to-end AI solutions, integrating LLMs and AI services (OpenAI, Anthropic, etc.) with enterprise platforms (ServiceNow, Salesforce, data platforms, internal systems).

Rapidly prototype, iterate, and deploy AI-enabled workflows, agents, copilots, and automations into real operational environments.

Serve as the technical bridge between product, engineering, data, and business stakeholders, ensuring solutions are technically sound, usable, and aligned with business value.

Drive solution architecture, including:

Prompt and workflow design

API integrations and orchestration

Enterprise knowledge integration)

Security, privacy, and governance considerations

Own solutions from concept → prototype → production → iteration, with acco

Senior Lead AI Engineer (AI Foundations, LLM Customization and Finetuning)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:
• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software com