Java Technical Lead (Java 17+, Gen AI, LLM)

ICONMA, LLC
  • Austin, TX
  • $60.71 Per Hour
  • Instant Apply
1 day ago

Job Description

Our client, an IT Services and Consulting company, is looking for a Java Technical Lead (Java 17+, Gen AI, LLM) for their Austin, TX/Hybrid location.
 
Responsibilities:

  • Enterprise GenAI Solution Architecture: Design and govern scalable, secure architectures embedding LLMs and foundation models into core business platforms and microservices backends.
  • Modern Java & Microservices Ecosystems: Architect and standardize microservices utilizing Java 17+ / Java 21, Spring Boot 3.x, and reactive patterns (Spring WebFlux), ensuring low latency, high throughput, and seamless integration with distributed caches and databases.
  • RAG & Agentic Workflows: Design and implement robust RAG pipelines, semantic caching, vector search indexing, and agent orchestration patterns (using frameworks like LangChain4j, Spring AI, Semantic Kernel, or custom orchestrators).
  • AI Governance, Security & Guardrails: Establish architectural guardrails for model security, prompt injection defenses, PII masking, data loss prevention (DLP), token cost optimization, and model evaluation/observability.
  • Distributed Scalability & Deployment: Champion event-driven integration using Apache Kafka, container orchestration via Docker and Kubernetes/Helm, and cloud-native AI deployments (AWS/GCP/Azure).
  • Technical Governance & Mentorship: Drive code quality, technical roadmaps, architecture review board (ARB) approvals, and guide engineering leads and delivery teams through complex integration challenges.
  • 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.
 
Requirements:
  • Deep enterprise engineering roots in modern Java (17+) and Spring Boot microservices. In this role, the selected candidate will define the architectural blueprint for integrating enterprise-grade Generative AI capabilities—including LLM orchestration, Retrieval-Augmented Generation (RAG), vector databases, and multi-agent workflows—into resilient, high-throughput microservices ecosystems.
  • The successful candidate will partner with the business, AI/ML research, platform engineering, and delivery stakeholders to deliver secure, production-hardened AI solutions.
  • Core Languages & Frameworks: Extensive enterprise experience in Java 17 or above, Spring Boot 3.x, Spring Cloud, and Spring Data.
  • GenAI & LLM Tooling: Hands-on experience integrating with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI, Bedrock, or open-source models) using Java-native AI frameworks (e.g., Spring AI, LangChain4j) or REST/gRPC wrappers.
  • RAG & Vector Stores: Deep understanding of embeddings, chunking strategies, hybrid search, and vector databases (e.g., pgvector, OpenSearch, Pinecone, Milvus, Qdrant).
  • Microservices Architecture: Proven expertise in distributed system patterns (SAGA, CQRS, Circuit Breaker, Event Sourcing) and real-time streaming architectures using Apache Kafka.
  • Databases: Hands-on proficiency with relational and NoSQL databases (PostgreSQL, Oracle, MongoDB, Redis).
  • Cloud & DevOps: Solid background in cloud architectures (AWS/GCP), container platforms (Docker, Kubernetes), and CI/CD automation pipelines.
  • 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.
  • 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.
  • 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).
  • Years of Experience:   12.00 Years of Experience
 
Why Should You Apply?Why Should You Apply?

Numbers & Facts

LocationAustin, TX
Salary$60.71 Per Hour

Skills

  • Agile Programming Methodologiesunmatched
  • Algorithmsunmatched
  • Amazon Web Services (AWS)unmatched
  • Apache Kafkaunmatched
  • Application Programming Interface (API)unmatched
  • Architectural Servicesunmatched
  • Artificial Intelligence (AI)unmatched
  • Automationunmatched
  • Best Practicesunmatched
  • Blueprintsunmatched
  • Business Modelunmatched
  • Cachingunmatched
  • Circuit Breakersunmatched
  • Cloud Architectureunmatched
  • Cloud Computingunmatched
  • Code Coverageunmatched
  • Code Reviewsunmatched
  • Continuous Deployment/Deliveryunmatched
  • Continuous Integrationunmatched
  • Cost Controlunmatched
  • Cost Modelingunmatched
  • Delivery Managementunmatched
  • DevOpsunmatched
  • Distributed Computingunmatched
  • Distributed Databasesunmatched
  • Dockerunmatched
  • Ecosystemsunmatched
  • Elasticsearchunmatched
  • Enterprise Architectureunmatched
  • GCP (Good Clinical Practices)unmatched
  • Gitunmatched
  • GitHubunmatched
  • GraphQLunmatched
  • Health Planunmatched
  • High Throughputunmatched
  • Information Technology Consultingunmatched
  • Injectionsunmatched
  • Integration Testingunmatched
  • JUnitunmatched
  • Javaunmatched
  • Java Platform Enterprise Edition (Java EE/J2EE)unmatched
  • Jenkinsunmatched
  • Kernel Programmingunmatched
  • Leadershipunmatched
  • Loss Preventionunmatched
  • Machine Toolunmatched
  • Mentoringunmatched
  • Message Brokerunmatched
  • Messaging Middlewareunmatched
  • Microservicesunmatched
  • Microsoft Windows Azureunmatched
  • MongoDBunmatched
  • NoSQLunmatched
  • Open Sourceunmatched
  • Oracleunmatched
  • PostgreSQLunmatched
  • Public/Media/Press/Analyst Relationsunmatched
  • Python Programming/Scripting Languageunmatched
  • Quality Assuranceunmatched
  • REST (Representational State Transfer)unmatched
  • RabbitMQunmatched
  • Redisunmatched
  • Regression Testingunmatched
  • Relational Databases (RDBMS)unmatched
  • Search Agentunmatched
  • Search Enginesunmatched
  • Semantic Searchunmatched
  • Shallow Parsingunmatched
  • Software Engineeringunmatched
  • Splunkunmatched
  • Spring Frameworkunmatched
  • Team Lead/Managerunmatched
  • Technical Deliveryunmatched
  • Technical Leadershipunmatched
  • Test Automationunmatched
  • Testingunmatched
  • eSourcingunmatched

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