Senior Agentic AI Full Stack Developer-Boston, MA(contract -100% remote considered)

Openkyber (Alaska, USA) Follow 3 hours ago

Senior Agentic AI Full Stack Developer Full Stack Engineer proficient in Python, with proven ability to build production-grade multi-agent AI systems , API s and UI

Key Responsibilities:

Build and deploy agentic AI systems multi-agent pipelines, LLM orchestration, tool-use, and RAG workflows
Design and develop production grade full stack applications and API's with Python and Golang backends
Integrate LLM APIs (OpenAI, Anthropic, Gemini) and open-source models into production applications
Build responsive, production-grade UIs that surface agentic AI capabilities to end users
Build data management pipelines for agents data ingestion, cleaning, chunking, and structured injection into vector stores and memory layers
Ensure data quality and consistency across agent context windows, retrieval pipelines, and tool inputs
Develop responsive frontend interfaces to surface AI capabilities to end users
Lead client-facing technical discussions requirements gathering, architecture walkthroughs, and delivery reviews
Take end-to-end technical ownership of engagements from PoC through production handoff
Collaborate with AI/ML and DevOps teams on inference stack integration and system observability

Requirements & Skills Must-Have:

5+ years of full stack engineering experience
Proficiency in Python and Golang for backend development
Hands-on experience building agentic AI systems LangChain, LangGraph, CrewAI, AutoGen, or equivalent
Strong UI/frontend skills with framework like React , with ability to design clean, functional interfaces
Familiarity with LLM APIs, cotext engineering, and RAG pipeline design
Experience with REST/gRPC API design and microservices architecture
Frontend development skills (React or equivalent)
Experience with vector databases (Pinecone, Weaviate, pgvector)
Exposure to observability tooling for AI systems (LangSmith, LangWatch, Helicone)
Strong communication skills able to lead client interactions and own technical narratives

Good to Have:

Containerization and cloud deployment (Docker, Kubernetes, AWS/Google Cloud Platform)
Familiarity with streaming inference and low-latency serving patterns

For applications and inquiries, contact:[email protected]

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