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.

BPX GenAI Squad Data Scientist requirement

Data Scientist AIML P2P3

Experience 6- 8 Years

Skillset Required

Expert level understanding of Machine LearningDeep Learning concepts techniques algorithms

Hands on working experience on building end to end MLDL solutions

Expert level proficiency in Python programming is a prerequisite

Strong understanding of objectoriented programming and design principles

Experienced with common data science packages in Python like Pandas Numpy Matplotlib and frameworks such as Tensorflow Pytorch

Handson experience in RESTful APIs development with FlaskAPI FastAPI

Excellent understanding of NLP concepts libraries including Word2Vec TFIDF NLTK SpaCy Gensim BERT GloVe etc

Must have experience in development of NLPNLGNLU projects

Deep understanding of Transformer Architectures including BERT GPT DistillBert

Good understanding of Generative AI concepts like Large Language Models Finetuning Evaluating LLMs PEFT RAG Embeddings Vector Databases etc

Experience in frameworks such LangChain LlamaIndex

Experience with Large Language models such as Llama GPT PaLM etc

Experience with Amazon Bedrock Azure OpenAI GCP GenAI Studio

Expertise in training and finetuning LLMs would be preferred

Proficientcy in model development deployment and optimization techniques

Certifications in GenAIAIML preferred

Experienced in deploying AI solutions in cloud environments

Working knowledge in any of the major cloud services AWSAzure

Working knowledge in either of AWS SageMakerAzure Cognitive ServicesGoogle Vertex AI

Certification in any of the Cloud Platforms AWSAzureGCP

Good problemsolving and critical thinking skills

Familiarity with version control systems Git

Knowledge of SQL NoSQL

Key Roles Responsibilities

Create and maintain highquality reusable code components and libraries for future use

Perform rigorous testing and validation to ensure models perform accurately and efficiently in various conditions

Miracle Software Systems, looking for a Generative AI Engineer to build cutting-edge AI applications powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).

If you’re passionate about building scalable AI systems that combine enterprise data with modern cloud and APIs, this role is for you.

Required Skills:
• 8+ years of software engineering experience
• Strong Python expertise
• Hands-on experience with LLMs / Generative AI
• Experience building RAG systems
• Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
• Strong experience with FastAPI / REST APIs
• Solid knowledge of SQL & data processing
• Experience with GCP
• Familiarity with Git & Docker

What You’ll Do:
• Design and develop Generative AI applications using LLMs
• Build and optimize RAG pipelines using embeddings and vector databases
• Develop scalable REST APIs using FastAPI or similar frameworks
• Apply prompt engineering and model optimization techniques
• Build and manage data pipelines for AI systems
• Deploy solutions on Google Cloud Platform (GCP)
• Implement Docker-based deployments and CI/CD pipelines
• Collaborate with cross-functional teams to integrate AI into enterprise systems

• *Job Description: AI Agent Engineer**

(Agent Building Team)
• Role:

AI Agent Engineer
• Job Location:

New Jersey
• Word Mode:

Hybrid
• Experience:

4+ years
• *About the Role**

We are looking for an AI Agent Engineer to join client’s Agent Building team to develop intelligent agents and business applications consuming the Enterprise AI Platform, with a focus on agent orchestration, evaluation frameworks, and domain-specific workflows using platform primitives.
• *Key Responsibilities**

· Build agents using AWS Strands SDK, Bedrock AgentCore SDK, and CrewAI orchestration

· Develop agent logic and troubleshooting using strong Python skills

· Implement comprehensive evaluation frameworks for model performance and RAG quality

· Create backend services with Python and integrate with platform APIs

· Build frontend experiences using React JS and Node JS frameworks

· Manage source code with Git/Bitbucket using agile development practices

· Design and debug agent behaviors for production reliability and business outcomes

· Integrate domain-specific RAG pipelines and evaluation metrics

· Consume platform services (gateways, MCP tools, observability) following security patterns
• *Required Skills & Qualifications**

· 4+ years Python development with AI/ML frameworks (CrewAI, LangChain, or equivalent)

· Hands-on experience building production agents with Bedrock AgentCore SDK, Strands SDK/CrewAI

· Strong evaluation framework development (LLM judging, RAG metrics, agent success criteria)

· Full-stack development experience (React JS frontend, Node JS/Python backend)

· Agent debugging and observability skills for complex multi-agent workflows

· Experience consuming enterprise API platforms (REST/GraphQL/OAuth2) securely
• *Nice to Have**

· Domain expertise in financial services use cases for agentic AI

· Multimodal agent development (text + image/audio processing)

· Previous CrewAI production deployments with custom tools and memory management
• Integers.