Senior AI Engineer — Remote Agentic AI Systems

artificial intelligence and robotics laboratory (itu air lab); Arlington (VA); On-site; USD 180,000 - 240,000; Full time

Job summary

Air seeks a Senior AI Engineer to join the Agentic AI team, scaling AI capabilities across the U.S. government.

You will design and build agent architectures, tool use, and evaluation systems, supporting production-grade AI across complex real-world problems. You will work across the AI stack from experimentation to production services, building scalable APIs and secure agent runtimes with a focus on reliability and performance.

Qualifications

• 5+ years of experience building production software, AI/ML systems, distributed systems, or similar technical systems.
• Deep experience designing, building, and operating production AI agents or agent platforms.
• Experience developing core agent infrastructure, including agent runtimes, tool execution, context management, memory, orchestration, or related platform capabilities.
• Strong understanding of state-of-the-art agent architectures and the engineering tradeoffs involved in building reliable, production-grade agentic systems.
• Experience designing agents that use tools, reason across multi-step tasks, interact with external systems, and operate over long-running or complex workflows.
• Experience building evaluation systems for agents, including task-level evaluations, behavioral evaluations, regression testing, and production quality measurement.
• Strong understanding of modern LLM systems, including model inference, context engineering, structured outputs, tool calling, retrieval, model selection, and techniques for improving agent performance.
• Strong programming experience in Python and experience building production-quality software.
• Experience designing scalable APIs, services, asynchronous systems, and event-driven architectures.
• Experience operating production services using Kubernetes and cloud platforms such as AWS, GCP, or Azure.

Responsibilities

• Design, build, and improve production agentic AI systems used to solve complex real-world problems.
• Develop agent architectures for reasoning, planning, tool use, context management, memory, and multi-step task execution.
• Build tools and capabilities that allow agents to securely interact with data, APIs, code, and external systems.
• Develop model and inference infrastructure supporting multiple commercial and open-weight language models.
• Evaluate new models, inference techniques, and emerging AI capabilities and determine how they can improve our production systems.
• Build automated evaluation frameworks to measure agent quality, reliability, task completion, and regressions.
• Develop datasets, benchmarks, and evaluation methodologies for complex agentic workflows.
• Improve agent performance through prompt and context engineering, model selection, tool design, inference strategies, and architectural improvements.
• Build scalable APIs, services, and infrastructure supporting agent execution and AI-powered product experiences.
• Design systems for asynchronous and long-running agent workflows.
• Build infrastructure for safe and reliable execution of agent-generated code and other computational workloads.
• Improve system observability through structured logging, metrics, distributed tracing, dashboards, and automated alerting.
• Investigate failures across models, agents, application code, and distributed infrastructure and turn those findings into systematic improvements.
• Optimize model and agent systems for latency, throughput, reliability, and infrastructure cost.
• Translate new AI research and emerging techniques into practical improvements to production systems.
• Work closely with product, platform, security, and domain teams to bring new AI capabilities from experimentation to production.

Skills

Production software

Agentic AI

Python

Kubernetes

Cloud platforms

Distributed systems

LLM systems

Tools

Kubernetes

AWS

GCP

Azure

Job description

Air seeks a Senior AI Engineer to join the Agentic AI team, scaling AI capabilities across the U.S. government.

You will design and build agent architectures, tool use, and evaluation systems, supporting production-grade AI across complex real-world problems. You will work across the AI stack from experimentation to production services, building scalable APIs and secure agent runtimes with a focus on reliability and performance.