Senior AI Engineer
About this role
Air needs a Senior AI Engineer to transition agentic AI systems beyond simple demos and prototypes into reliable, production-grade software that solves complex real-world problems for government agencies and industrial suppliers. This engineering hire will work within the Agentic AI team to scale capabilities for the AI agent, Ace, focusing on the intersection of applied artificial intelligence and systems engineering. Responsibilities include designing agent architectures, managing model integrations, building tools, and establishing evaluation systems across the entire AI stack.
Successful candidates will thrive by building solutions to intricate technical challenges while operating effectively at the frontier of a rapidly evolving field. Ideal practitioners understand that creating robust AI products involves much more than simply calling a model application programming interface. Professionals who enjoy reasoning about context, memory, tools, and compute to construct dependable production systems will find this opportunity a strong fit.
What you will do
- Design, build, and improve production agentic AI systems to solve complex real-world problems.
- Develop agent architectures that handle reasoning, planning, tool use, context management, memory, and multi-step task execution.
- Build tools and capabilities that allow agents to interact securely with data, application programming interfaces, code, and external systems.
- Develop model and inference infrastructure supporting multiple commercial and open-weight language models.
- Build automated evaluation frameworks to measure agent quality, reliability, task completion, and regressions.
- Optimize model and agent systems for latency, throughput, reliability, and infrastructure cost.
- Collaborate with product, platform, security, and domain teams to transition new AI capabilities from experimentation into production.
What you need
- Five or more years of experience building production software, artificial intelligence and machine learning systems, distributed systems, or similar technical environments.
- Deep experience designing, building, and operating production artificial intelligence agents or agent platforms.
- Strong understanding of modern large language model systems, including inference, context engineering, tool calling, retrieval, and model selection.
- Strong programming experience in Python along with experience building production-quality software.
- Experience designing scalable application programming interfaces, services, asynchronous systems, and event-driven architectures.
- Experience operating production services using Kubernetes and cloud platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure.
- United States citizenship is required for this position.
Nice to have
- Current possession of a United States security clearance, or the ability to obtain one with sponsorship
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Experience building secure code execution environments or sandboxes for artificial intelligence agents
- Experience with multi-agent architectures, agent-to-agent communication, or distributed agent execution
- Experience with fine-tuning, post-training, reinforcement learning, or synthetic data generation
Skills and tech stack
Questions candidates ask
Where is this job located and what is the remote policy?
This role is a full-time position based in the Pittsburgh, Pennsylvania office or open to remote opportunities. It may require up to 25% travel, including periodic travel to the Pittsburgh, Pennsylvania and Arlington, Virginia offices for team collaboration, planning activities, and in-person meetings.
What citizenship or clearance requirements apply to this role?
United States citizenship is required for this position. Candidates may also have the current possession of a United States security clearance, or the ability to obtain one with company sponsorship.
What kind of systems and tech stack will I be working with?
You will design and build agent architectures, model integrations, tools, evaluation systems, and infrastructure that enable increasingly capable artificial intelligence systems. The work involves Python programming, Kubernetes, cloud platforms like Amazon Web Services, Google Cloud Platform, or Microsoft Azure, and modern large language model systems.