Technical Lead - GenAI & Java Microservices

We are seeking a hands-on Technical Lead specializing in Java 17+ and Spring Boot microservices with practical experience implementing Generative AI features. You will bridge architecture and execution, guiding a team of engineers in building, optimizing, and deploying AI-augmented microservices, fine-tuning RAG retrieval systems, and ensuring clean, resilient enterprise code.

What are the top skills required for this role?

• Modern Java & Microservices Core: Extensive hands-on expertise in Java 17+, Spring Boot 3.x, REST/Reactive APIs, and distributed microservices architecture.
• Enterprise GenAI & LLM Integration: Practical experience with LLM orchestration, frameworks like Spring AI or LangChain4j, RAG pipelines, prompt engineering, and guardrails/security.
• Vector Databases & Data Ecosystem: Proficiency in semantic search tools and vector stores (e.g., pgvector, OpenSearch), alongside messaging queues (Apache Kafka) and enterprise databases (PostgreSQL/Oracle)., * Hands-on Engineering & Delivery: Lead the technical implementation of Java-based microservices integrating GenAI capabilities, intelligent automation pipelines, and enterprise data connectors.
• RAG & Prompt Engineering Execution: Build and maintain RAG pipelines, fine-tune retrieval algorithms, implement semantic vector lookups, and design structured prompt templates with robust validation.
• Microservices Development: Write and review production-grade, high-performance code in Java 17+ and Spring Boot, implementing REST/GraphQL endpoints, Kafka consumers/producers, and asynchronous event processing.
• Testing & Quality Assurance: Drive high code coverage with JUnit 5, Mockito, and TestContainers; establish automated testing for GenAI outputs (groundedness, hallucination detection, prompt regression testing).
• Team Leadership & Sprint Governance: Conduct PR code reviews, mentor engineers on best practices (including developer productivity tools like GitHub Copilot/Claude Code), manage sprint deliverables, and resolve technical blockers.
• Production Operations: Partner with SRE/DevOps to monitor service health, token usage, latency bottlenecks, and logging/observability using tools like Splunk, Grafana, or OpenTelemetry.

• Programming & Core Stack: Strong proficiency in Java 17+, Spring Boot, and Microservices architecture.
• GenAI Frameworks & Integrations: Practical experience using Spring AI, LangChain4j, or Python AI service wrappers to interface with foundational models and build agentic/RAG workflows.
• Vector Databases & Search: Working familiarity with vector search extensions and engines (e.g., pgvector, OpenSearch, ChromaDB, or Elasticsearch).
• Data & Messaging: Practical experience with PostgreSQL or Oracle, alongside message brokers like Apache Kafka or RabbitMQ.
• Testing & Modern Engineering: Strong foundation in unit, integration, and contract testing (JUnit, TestContainers), Git workflows, and CI/CD pipelines (Jenkins, GitHub Actions).
• Leadership & Collaboration: Demonstrated success in leading a team of 4-8 engineers, conducting code reviews, estimating technical stories, and collaborating across distributed teams.