Partner with Agentic AI scientists and engineers to design, build, and deploy AI agents that automate and optimize complex workflows
Support both R&D and customer-facing programs, accelerating the transition of applied AI research into operational impact
Develop software and infrastructure for agent communication, API integration, orchestration, monitoring, testing, and deployment
Build and maintain agentic workflows using open-source and commercial LLMs, agent frameworks, and retrieval systems
Design approaches for evaluating and securing AI agents, ensuring reliability, performance, and trustworthy outcomes
Ensure AI systems align with ethical, transparency, fairness, and security principles

Bachelor’s degree in Computer Science, Engineering, or related field with 4+ years of directly related experience in AI / Automation / MLOps
Strong intellectual curiosity and ability to work independently
Experience developing agentic AI systems, including planning–execution–reflection loops, multi-agent coordination, tool use, API integration, RAG, and memory/context management
Hands-on experience with generative AI and NLP techniques including prompt engineering, semantic search, summarization, and entity extraction
Working knowledge of LLMs and frameworks such as LangChain, LangGraph, CrewAI, AutoGen, MCP, or A2A
Experience with vector databases such as Pinecone, Weaviate, or FAISS
Proficiency in Python and modern software engineering practices
Familiarity with SDLC and DevSecOps methodologies
Experience deploying applications in containerized or virtualized environments such as Docker, Kubernetes, or VMware
Ability to mentor junior engineers and contribute within collaborative technical teams
U.S. citizenship required with ability to obtain a Secret clearance.

AI Engineer

Key skills