Custom Software Engineer

Project Role : Custom Software Engineer Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs. Must have skills : Digital Full Stack Development Good to have skills : TypeScript, Python (Programming Language), Software Development Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As an AI Native Software Engineer, your day revolves around creating and delivering software solutions where artificial intelligence is deeply integrated into every stage of development. You will engage in designing, building, and deploying applications that leverage AI capabilities, ensuring that these solutions meet high standards of quality and compliance. Your role involves continuous refinement of software processes to enhance efficiency and reliability, collaborating with various teams to innovate and improve the overall software lifecycle. This position offers an opportunity to work at the forefront of technology, blending software engineering with AI-driven methodologies to produce impactful products. Roles & Responsibilities: -Design and implement multi-agent orchestration pipelines using LangGraph state machines with conditional routing, self-healing loops, and sub-agent hierarchies - Build and maintain a hybrid retrieval system combining Neo4j knowledge graphs (Cypher) with Qdrant vector search and sentence-transformer embeddings - Develop FastAPI backend services with async I/O (asyncpg, Motor), Pydantic v2 models, and JWT/RBAC security - Build React 18 / TypeScript frontend features including visual graph editors (ReactFlow), real-time SSE streaming, and observability dashboards (Recharts) - Integrate enterprise protocols: A2A (JSON-RPC), MCP (Model Context Protocol), AG-UI (Server-Sent Events) - Connect to ALM/PLM tools via REST and GraphQL APIs with OAuth2/SSO authentication (SAML, OIDC) - Implement dual-tier agent memory (Redis L1 + mem0 L2) with semantic recall and context consolidation - Build DAG-based workflow compilation with topological sorting, cycle detection, and Ray-based parallel execution - Deploy and operate containerized services using Docker, Azure Bicep IaC, and CI/CD pipelines (Azure Pipelines / Jenkins) - Serve and manage on-prem LLM models via vLLM alongside cloud-hosted models (OpenAI-compatible APIs) Professional & Technical Skills: Backend & AI - Python 3.10+ — production-grade FastAPI, Pydantic v2, async/await patterns - LangGraph / LangChain — state machines, tool calling, agent orchestration - LLM engineering — prompt design, token budgeting, multi-model routing, self-healing retry loops - PostgreSQL (JSONB, asyncpg) or MongoDB (Motor) — async data persistence Knowledge & Retrieval - Neo4j — Cypher queries, entity-relationship graph modeling, traversal algorithm