Full Stack Engineer

We are seeking an engineer who is exceptional in Java Spring boot, 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.

Duties and Responsibilities

• Lead a team of Offshore Engineers and deliver successful iterations of AI initiatives.

• Build backend services in Springboot, Python using Flask, FastAPI, or Django. design clean APIs, background jobs, and integrations.

• Develop user interfaces with React or Angular; collaborate on UX and component libraries; ensure accessibility and performance.

• Own quality with PyTest (including fixtures, parametrization, coverage), integration tests, and contract tests; enable CI test automation.

• Ship GenAI features: design prompts, tools, memories, and workflows, implement RAG pipelines, orchestrate agentic systems.

• Productionize AI with guardrails for safety, compliance, observability, and fallback strategies; measure quality (latency, cost, accuracy).

• Work across data layers: vector stores, embeddings, caching, and secure connectors; uphold data privacy and governance.

• Collaborate with product, design, and platform teams, review code, architect solutions, document decisions, and mentor peers.

Key Skills

• 10+ years of experience in design, development, and triaging for large, complex systems.

• Experience in Java and object-oriented design skills

• 5+ years of microservices development

• 3+ years working in Spring boot

• Experienced using API dev tools like IntelliJ/Eclipse, Postman, Git, Cucumber

• Hands on experience in building microservices based application using Spring boot and REST, JSON

• DevOps understanding – containers, cloud, automation, security, configuration management, CI/CD experience in streaming technologies like Apache Kafka.

• Gen AI

• Java Spring boot Microservices

Python & Backend (5+ years of experience)

• Expert level Spring boot and Python (typing, async, packaging, linting: black/ruff/flake8, performance profiling).

• Web frameworks: Flask, FastAPI, Django (routing, middleware, ORM, auth, background tasks).

• API design (REST/JSON), OpenAPI/Swagger, pagination, idempotency; secure patterns (OAuth/OIDC, JWT, RBAC).

Frontend (3+ years of experience)

• React or Angular: component design, state management, routing, forms, accessibility (WCAG), unit/e2e tests (Jest, Playwright).

• Build tooling: Vite/Webpack, npm/yarn

GenAI / Agentic AI (1 year of experience)

• LLM concepts: tokenization, context windows, embeddings, temperature/top p, system prompts, tool/function calling.

• RAG: ingestion pipelines, chunking strategies, metadata, types of RAG (basic, hierarchical, hybrid, multi vector, agent routed), evaluators.

• Agents & Agentic AI: planning/execution loops, tool orchestration, memory, multi agent collaboration, error handling.

• MCP (Model Context Protocol): designing tools/resources, host applications, capability negotiation, secure tool exposure.

• Guardrails: input/output filtering, policy enforcement, prompt injection resilience, PII controls, jailbreak detection, red teaming.

• Open source frameworks: CrewAI, LangGraph/LangChain (nodes/edges, executors, runnables, toolkits). Familiarity with alternatives (Haystack, LlamaIndex) is a plus.

Data & Infra (3-5 years of experience)

• Vector DBs, Relational DBs (PostgreSQL, MySQL) and Caching (Redis).

• Cloud & DevOps: containers (Docker), orchestration (Kubernetes), CI/CD, secrets management; monitoring/observability (logs, traces, metrics).

• Performance & cost management for LLM workloads. Batch vs. streaming jobs. Queuing (MQ, Kafka).

Nice-to-have/Advantage

• LLM Observability, Guardrails, Vector database, Graph Database