Role Overview 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). Key Responsibilities • 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. Required Technical Skills & Qualifications • 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.
Applicant Notices & Disclaimers
For information on benefits, equal opportunity employment, and location-specific applicant notices, click here
At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.The pay rate for this position is $61.00/hr.