Production AI Engineer: Multi-Agent Orchestration

Tactical Edge; Washington (District of Columbia); On-site; USD 150,000 - 210,000; Full time

Job summary

Tactical Edge is seeking an engineer to build autonomous AI systems that reason, plan, and execute in production environments. You will design multi-agent architectures, orchestration pipelines, and tool-use frameworks powering enterprise AI solutions.

This is a production-focused role with agents running 24/7 in enterprise settings, requiring strong Python skills, async programming, and a deep understanding of LLM internals.

Qualifications

• Strong Python skills with deep understanding of async patterns and systems design.
• Understands LLM internals (tokenization, attention, context management) beyond API wrappers.
• Production-minded: reliability, observability, and failure modes from day one.
• Comfortable with ambiguity and evolving requirements.
• 3+ years building with LLMs in production environments.
• Experience with agentic frameworks (LangGraph, CrewAI, AutoGen, or custom).
• Strong systems programming skills and familiarity with AWS AI services (Bedrock, SageMaker, ECS).
• Understanding of prompt engineering, RAG architectures, and retrieval systems.

Responsibilities

• Design and build multi-agent systems that operate in production environments.
• Implement tool-use, function calling, and agentic workflows with robust error handling and observability.
• Optimize prompts, manage context windows, and deploy efficient AI pipelines (RAG, retrieval).
• Work with models from Anthropic, OpenAI, and open-source ecosystems.
• Deploy and monitor agents on AWS services with reliability and governance controls.

Skills

Python

Async patterns

Systems design

Agentic frameworks

LLMs in production

Tools

LangGraph

CrewAI

AutoGen

AWS Bedrock

SageMaker

ECS

Job description

Tactical Edge is seeking an engineer to build autonomous AI systems that reason, plan, and execute in production environments. You will design multi-agent architectures, orchestration pipelines, and tool-use frameworks powering enterprise AI solutions.

This is a production-focused role with agents running 24/7 in enterprise settings, requiring strong Python skills, async programming, and a deep understanding of LLM internals.