Senior AI Engineer
New
A
AirEnterprise AI
Arlington, Virginia, United States; Pittsburgh, Pennsylvania, United States; RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonGCPKubernetesMachine LearningAzureLLMDistributed Systems
Requirements
- 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.
- Strong understanding of state-of-the-art agent architectures and engineering tradeoffs.
- Experience designing agents that use tools, reason across multi-step tasks, and operate over complex workflows.
- Experience building evaluation systems for agents, including task-level evaluations and regression testing.
- Strong understanding of modern LLM systems, including inference, context engineering, and tool calling.
- Strong programming experience in Python and experience building production-quality software.
- Experience designing scalable APIs, services, and asynchronous systems.
- Experience operating production services using Kubernetes and cloud platforms such as AWS, GCP, or Azure.
- Strong understanding of distributed systems, containers, service orchestration, networking, and storage.
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.
- Build scalable APIs, services, and infrastructure supporting agent execution and AI-powered product experiences.
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