Senior AI Software Engineer | AI Agents | Python | F2F Interview in NJ - W2 Role at TMSLLC – Jersey City | Jobyssey

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

All your information will be kept confidential according to EEO guidelines.

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