Full Time

Sr. AI Engineer – Agent Orchestration - Averity - Pittsburgh, PA

Averity

Pittsburgh, PA
Posted 10 days ago

Sr. AI Engineer – Agent Orchestration

A high-growth technology company building AI-powered software for US government customers is hiring a Senior AI Engineer focused on agent workflow orchestration. The company’s AI agent has seen rapid adoption, and the team is now pushing it to handle increasingly complex, multi-step tasks either fully autonomously or in a human-in-the-loop mode.

This role is squarely backend and systems-focused. You’ll be designing how an AI agent plans, sequences, and executes long-running workflows — coordinating across multiple tools, data sources, and sub-agents to complete jobs that today require hours of manual work. Think of it as building the brain and nervous system of the agent, not the hands.

What You’ll Do

Architect and build the workflow engine that powers multi-step agent task execution — including planning, sequencing, branching, error recovery, and human handoff pointsDesign and implement multi-agent coordination patterns: routing between specialized sub-agents, managing shared memory and context, and orchestrating parallel workstreamsBuild scalable tool-use infrastructure that lets agents dynamically discover, select, and chain tools based on task requirementsOwn reliability and observability for long-horizon agent tasks — designing checkpointing, retry strategies, and evaluation harnesses that catch failures before users doDefine and enforce the technical architecture and engineering standards for agentic systems across the platform

What We’re Looking For

You have built an LLM reliably completing complex, multi-step tasks in production — not just single-turn Q&A, but real workflows with branching logic, tool calls, and failure handlingDeep experience with workflow orchestration patterns (DAGs, state machines, event-driven architectures) applied to LLM-powered systemsHands-on experience with agent frameworks (Claude Agent SDK, OpenAI Agent SDK, LangGraph, or similar)Strong understanding of LLM reliability e