Senior AI Software Engineer | AI Agents | Python | F2F Interview in NJ
- Contract
Job Description
Role: Senior AI Software Engineer (Agentic AI / AI Agents)
Location: Hybrid
Duration: 12+ Months
Interview: In-Person
Job Summary
We are seeking a hands-on Senior AI Software Engineer with strong experience in designing, building, and deploying production-grade Agentic AI systems. The ideal candidate should have expertise in developing AI Agents capable of multi-step reasoning, tool orchestration, Retrieval-Augmented Generation (RAG), and secure enterprise AI solutions.
This is NOT a traditional Java/.NET Full Stack or chatbot integration role. We are specifically looking for engineers with real-world production experience building AI Agents using Python and modern Agentic AI frameworks.
Required Skills
- 5–10+ years of Software Engineering experience.
- Strong hands-on experience with Python and backend development (FastAPI preferred).
- Experience building and deploying production AI Agents / Agentic AI applications.
- Strong experience with LangGraph, LangChain, CrewAI, AutoGen or similar AI Agent frameworks.
- Hands-on experience with:
- Retrieval-Augmented Generation (RAG)
- AI Agent Architecture
- Multi-Agent Systems
- Tool Calling / Function Calling
- Agent Memory
- Prompt Engineering
- Embeddings
- Experience with Vector Databases such as Pinecone, FAISS, Weaviate, ChromaDB, or Azure AI Search.
- Experience deploying LLM applications using OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, Google Vertex AI, or Llama models.
- Strong experience with Docker, Kubernetes, CI/CD, LLMOps, Monitoring & Observability.
- Experience working on AWS, Azure, or GCP.
- Strong understanding of AI Security, Guardrails, Prompt Injection Protection, PII Handling, RBAC, and Responsible AI.
Responsibilities
- Design and develop enterprise-scale Agentic AI solutions.
- Build AI Agents capable of planning, reasoning, tool usage, and multi-step task execution.
- Develop reusable AI Agent frameworks, SDKs, and RAG pipelines.
- Build secure AI services with proper guardrails, approval workflows, retries, and fault tolerance.
- Implement production LLMOps, monitoring, evaluation, observability, and performance optimization.
- Collaborate with Product Managers, Data Scientists, and Engineering teams to deliver scalable AI platforms.
Preferred Experience
- LangGraph
- MCP (Model Context Protocol)
- AI Agent Evaluation Frameworks
- Healthcare, Banking, Insurance, or other regulated industry experience
Additional Information
All your information will be kept confidential according to EEO guidelines.
By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website's terms and privacy policy apply