Technical Lead – GenAI & Java Microservices

Job Title: Technical Lead – GenAI & Java Microservices Location: Hybrid – Austin, TX Experience: 12+ Years Job Summary We are seeking an experienced, hands-on Technical Lead – GenAI & Java Microservices with strong enterprise engineering expertise in Java 17+ and Spring Boot microservices, along with practical experience implementing Generative AI solutions. The ideal candidate will lead the design, development, and deployment of AI-enabled microservices, integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and agentic workflows into scalable enterprise platforms. This role combines technical architecture, hands-on engineering, team leadership, and production delivery. Key Responsibilities GenAI Architecture & Integration Design and implement enterprise-grade GenAI solutions integrating LLMs and foundation models into business applications and microservices. Build and maintain RAG pipelines, semantic search, vector indexing, and agent orchestration workflows. Implement prompt engineering, structured prompt templates, and retrieval optimization. Integrate LLM services such as OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, and open-source models. Establish AI security guardrails, including prompt injection protection, PII masking, data loss prevention, and token cost optimization. Java & Microservices Development Lead development of production-grade applications using Java 17+, Java 21, and Spring Boot 3.x. Design scalable microservices using Spring Cloud, Spring Data, and reactive programming patterns such as Spring WebFlux. Develop REST/GraphQL APIs, Kafka producers and consumers, and asynchronous event-processing solutions. Implement distributed system patterns such as SAGA, CQRS, Circuit Breaker, and Event Sourcing. Ensure high performance, reliability, maintainability, and code quality. Technical Leadership & Delivery Guide and mentor engineering teams of approximately 4–8 developers. Conduct code reviews, establish engineering standards, and manage technical deliverables. Lead sprint planning, technical estimation, and resolution of engineering blockers. Collaborate with architecture, AI/ML, platform engineering, business, and delivery teams. Drive architecture reviews, technical roadmaps, and enterprise engineering best practices. Testing & Production Operations Establish automated testing practices using JUnit 5, Mockito, and TestContainers. Implement GenAI testing for groundedness, hallucination detection, and prompt regression. Partner with SRE and DevOps teams to monitor application health, latency, token usage, and service performance. Use observability tools such as Splunk, Grafana, and OpenTelemetry. Support CI/CD automation and production deployments. Required Technical Skills & Qualifications Core Java & Microservices Extensive hands-on experience with Java 17+ and Spring Boot 3.x. Strong knowledge of Spring Cloud, Spring Data, REST APIs, and reactive programming. Proven experience designing and developing enterprise microservices architectures. Knowledge of distributed systems and event-driven architecture. Generative AI & LLM Practical experience integrating LLM APIs such as OpenAI, Anthropic Claude, Azure OpenAI, or AWS Bedrock. Experience with Java-native AI frameworks such as Spring AI or LangChain4j. Hands-on knowledge of RAG pipelines, embeddings, chunking strategies, semantic search, and prompt engineering. Understanding of agentic workflows, LLM orchestration, and AI security guardrails. Vector Databases & Data Technologies Experience with vector databases and search technologies such as pgvector, OpenSearch, Pinecone, Milvus, Qdrant, ChromaDB, or Elasticsearch. Strong database experience with PostgreSQL, Oracle, MongoDB, or Redis. Experience with Apache Kafka or RabbitMQ. Cloud & DevOps Experience with cloud platforms such as AWS, GCP, or Azure. Knowledge of Docker, Kubernetes, and Helm. Experience with CI/CD tools such as Jenkins and GitHub Actions. Familiarity with production monitoring, logging, and observability tools. Testing & Team Leadership Strong experience with JUnit, Mockito, TestContainers, and automated testing. Experience leading engineering teams of 4–8 developers. Strong code review, mentoring, technical estimation, and sprint management skills. Ability to collaborate with distributed teams and cross-functional stakeholders. Top Required Skills Java 17+ & Spring Boot 3.x: Strong enterprise development and microservices architecture experience. Generative AI & LLM Integration: Hands-on experience with Spring AI, LangChain4j, LLM orchestration, RAG pipelines, and prompt engineering. Vector Databases & Semantic Search: Experience with pgvector, OpenSearch, Pinecone, or similar technologies. Distributed Systems & Messaging: Apache Kafka, event-driven architecture, and distributed design patterns. Technical Leadership: Experience mentoring engineers, conducting code reviews, and leading technical delivery.