Generative AI Technical Lead / Solution Architect Java, Python & Full Stack

• -Translate business requirements into solution architecture, technical designs, and implementation plans.
• -Develop enterprise applications using Java, Spring Boot, Python, FastAPI, and React or Angular.
• -Design REST APIs and asynchronous services for AI inference, retrieval, document ingestion, and enterprise integration.
• -Build GenAI solutions for conversational assistance, document processing, summarization, and knowledge discovery.
• -Implement RAG pipelines covering ingestion, parsing, chunking, metadata enrichment, embeddings, indexing, retrieval, reranking, and citations.
• -Implement vector similarity search, keyword search, and hybrid retrieval.
• -Build knowledge graphs and graph-based retrieval to Client relationships across entities and documents.
• -Implement recursive retrieval and multi-hop search, progressively retrieving related content to answer complex questions.
• -Combine vector retrieval with graph traversal where the use case requires both semantic relevance and relationship context.
• -Develop agent workflows with tool calling, state management, recovery, and human review.
• -Integrate AI services with enterprise APIs, databases, and business workflows.
• -Evaluate retrieval and generation quality, including accuracy, grounding, relevance, latency, and cost.
• -Apply security, privacy, access controls, and responsible AI practices.
• -Deploy and operate solutions on Azure or AWS.
• -Contribute directly to coding, reviews, testing, debugging, and performance Eligible to workimization.
• -Maintain architecture documents, API specifications, data flows, and deployment guides.
• -Collaborate with stakeholders, communicate technical tradeoffs, and mentor engineering teams.

We are seeking a hands-on technical lead with strong experience in Generative AI, large language models, Java full stack development, Python, FastAPI, and enterprise solution architecture. The candidate will design and develop AI-enabled applications using vector search, knowledge graphs, and recursive retrieval, integrate them with enterprise systems, and guide delivery through production deployment.

The role requires practical coding experience and strong communication and stakeholder management skills., * Generative AI and LLMs - Python and FastAPI

• Vector, Graph, and Recursive Search - Understanding of graph traversal, multi-hop retrieval, and GraphRAG patterns.Java Full Stack Development
• Architecture and Cloud - Hands-on experience with Azure or AWS, including AI services, compute, storage, identity, secrets management, and monitoring.
• Familiarity with Docker and Kubernetes. Communication and Stakeholder Management, * Walk through a GenAI application they personally implemented and identify their coding contributions.
• Demonstrate Python/FastAPI and Java/Spring Boot API development skills.
• Explain a RAG pipeline and how retrieval quality and grounding were evaluated.
• Describe when to use vector search, graph traversal, and recursive retrieval.
• Explain safeguards for multi-hop retrieval, including stopping conditions and evidence traceability.
• Discuss cloud deployment, production troubleshooting, and stakeholder communication using concrete examples.