Full Stack Engineer (Java & Python AI)

We are seeking an engineer who is exceptional in Java Springboot, experienced with web frameworks (Flask, FastAPI, Django), comfortable building frontends (React, Angular), and capable of delivering production-grade GenAI solutions (LLMs, RAG, Agents/Agentic AI, MCP, guardrails). Candidate should be able to design, build, and operate services and applications that leverage modern AI patterns with strong software craftsmanship.

Key Responsibilities

• Backend & API Development: Build robust backend services and APIs using Java Spring Boot and Python frameworks like Flask, FastAPI, or Django.
• GenAI & Agentic Solutions: Design and implement Large Language Model (LLM) features, Retrieval-Augmented Generation (RAG) pipelines, memory systems, prompts, and agentic workflows.
• Full-Front-End Work: Create user interfaces with React or Angular.
• Data & Infrastructure: Handle vector stores, embeddings, caching, and secure data connectors.
• Quality & Testing: Manage testing using PyTest, integration tests, CI automation, and implement AI guardrails and observability.

Qualifications:

• 10+ years of software engineering experience in designing, developing, troubleshooting, and supporting large, complex systems.
• Strong Java/Spring Boot Microservices expertise – 5+ years of microservices development and 3+ years of Spring Boot, with hands‑on experience in REST/JSON APIs and object-oriented design.
• Advanced Python backend development – 5+ years of Python experience, including Flask/ FastAPI/ Django, API design, asynchronous programming, testing, packaging, and performance optimization.
• GenAI / Agentic AI experience – At least 1 year of hands‑on experience with LLMs, RAG, agentic workflows, tool/function calling, MCP, embeddings, guardrails, and frameworks such as LangGraph/LangChain or CrewAI.
• Full-stack, cloud, and DevOps capabilities – 3+ years with React or Angular, plus experience with Docker, Kubernetes, CI/CD, Kafka, databases/vector DBs, Redis, cloud infrastructure, and observability.