Note: The job is a remote job and is open to candidates in USA. Air is seeking a Senior AI Engineer to build production-grade agentic AI systems and infrastructure for complex real-world problems. The role spans agent architectures, model integrations, evaluation systems, and scalable services, taking AI capabilities from experimentation into production.
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
- U.S. Citizenship is required
- 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
- Demonstrated ability to evaluate emerging models, research, and agent techniques and translate promising approaches into production systems
- 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
- Strong understanding of distributed systems, containers, service orchestration, networking, storage, and scalable architectures
- Comfortable debugging complex failures spanning model behavior, agent execution, application code, and production infrastructure
- Able to move quickly between research and engineering: prototype an idea, evaluate it rigorously, understand why it works or fails, and turn successful approaches into reliable production systems
- Comfortable working at the frontier of a rapidly evolving field where established patterns may not yet exist
- Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Experience building secure code execution environments or sandboxes for AI 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
- Experience building AI observability, tracing, and debugging infrastructure
- Experience optimizing inference latency, throughput, GPU utilization, or model-serving costs
- Experience with AI security, adversarial testing, or securing agentic systems
- Experience working in government, defense, or other mission-critical environments
Benefits
- This role is a full-time position based in our Pittsburgh, PA office or open to Remote Opportunities.
Company Overview