AI Engineer (Mid–Senior) AI Agents US Citizens only Federal
Menlo Park, CA, United States
A USD 100K-140K (estimate) Mid-level Full Time
Tasks
- Add logging auditing and data access controls
- Build data pipelines for document ingestion and embeddings
- Containerize and deploy applications using CI CD
- Design and build AI agents
- Develop Python services and APIs
- Develop RAG applications
- Develop testing and evaluation for AI agents and RAG
- Document architectures and operational procedures
- Implement authentication and authorization
- Implement vector search and retrieval
- Integrate LLM applications with enterprise data and APIs
- Mentor junior AI engineer
- Monitor and troubleshoot production AI applications
- Support AI control plane for monitoring governance and usage tracking
Perks/Benefits
Skills/Tech-stack
API Integration | AWS Bedrock | Auditing | Authentication | Authorization | Autogen | Azure AI | CI/CD | Context Management | CrewAI | Data Pipelines | Docker | Embeddings | Evaluation | Faiss | Gemini for Government | Git | Google Gemini | Google Gemini for Government | Google Vertex | Google Vertex AI | Infrastructure as Code | Kubernetes | LLM Applications | Langchain | Langgraph | Language Models | Large Language Models | Logging | Microsoft Copilot | Milvus | Observability | OpenSearch | PGVector | Pinecone | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | Semantic Kernel | Terraform | Vector Databases | Vector Search | Vertex AI | Weaviate | “as-code”
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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