AI Implementation Engineer - JobID-0245

What you'll do

• Build and evaluate agentic AI systems, conversational interfaces, and RAG pipelines for operational use.
• Integrate LLMs, tools, APIs, data sources, and MCP interfaces; optimize local CPU/GPU infrastructure and offline update processes.
• Gather requirements, collaborate with engineering and mission teams, and document, test, and improve AI solutions.

What they ask for

• Bachelor’s degree in a listed technical field or equivalent full-time professional experience.
• 5-10+ years of professional experience in software engineering, machine learning engineering, AI engineering, or related technical roles.
• Proficiency in Python, including NumPy and Pandas; hands-on experience with production local inference engines such as vLLM, SGLang, Triton Inference Server, or TensorRT-LLM.
• Experience with a modern AI/ML framework, Linux and hardening, commercially available AI tooling, hosting LLM servers and models, distributed networking, and containerization.

Nice to have

• Master’s degree in Engineering or another technical field.
• Experience with local GPU hosting, AI gateways, model optimization, tool calling, RAG, vector stores, MCP, or container orchestration.

Pay

$114,000 - $184,000 USD base salary; $135,000 - $231,000 USD base salary

Tools

Python, NumPy, Pandas, vLLM, SGLang, Triton Inference Server, TensorRT-LLM, PyTorch

AI focus

Builds agentic AI, LLM integrations, RAG pipelines, and production AI workflows for on-premises, air-gapped environments; includes local inference and model optimization.