VortexLink

Compensation

Full Description

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 s 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