Java AI Engineer / AI Engineer (Java backend)

Job Description: AI Engineer (Java Backend) Experience: 11+ Years Employment Type: Full-Time (Contract W2 only) About the RoleWe are looking for a seasoned AI Engineer with a strong Java backend foundation to design, build, and scale production-grade AI/ML-powered systems. This role sits at the intersection of enterprise Java engineering and applied AI — you'll be responsible for integrating LLMs, building intelligent services, and ensuring these systems are robust, scalable, and production-ready within a Java-centric ecosystem. Key ResponsibilitiesDesign and develop scalable backend services in Java (Spring Boot/Spring Framework) that integrate AI/ML and LLM-based capabilities into enterprise applications.Architect and implement RAG (Retrieval-Augmented Generation) pipelines, vector search, and semantic retrieval systems.Integrate with LLM providers (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, etc.) via APIs, and build robust prompt-engineering and orchestration layers.Build and maintain microservices architectures exposing AI capabilities (REST/gRPC APIs) for internal and external consumption.Own end-to-end MLOps/LLMOps practices — model versioning, deployment pipelines, monitoring, and observability for AI services.Collaborate with Data Science/ML teams to productionize models, embeddings, and inference pipelines at scale.Design for performance, low latency, and high throughput, applying caching, async processing, and message queue patterns (Kafka, RabbitMQ).Implement vector databases (Pinecone, Weaviate, Milvus, pgvector, Elasticsearch) for semantic search and knowledge retrieval use cases.Drive best practices around security, data privacy, and responsible AI (PII handling, guardrails, hallucination mitigation).Mentor junior engineers, conduct code/design reviews, and contribute to architectural decision-making as a technical leader.Partner with product and business stakeholders to translate requirements into scalable technical solutions.Evaluate and prototype emerging frameworks/tools (LangChain4j, Spring AI, LlamaIndex, Semantic Kernel) for enterprise fit.Required Skills & Experience11+ years of hands-on software engineering experience, with deep expertise in Core Java, Java 11/17+, Spring Boot, Spring Framework.Proven experience (2+ years) building AI/LLM-integrated applications — prompt engineering, embeddings, RAG, agentic workflows, or ML model serving.Strong understanding of microservices, distributed systems, and API design (REST, GraphQL, gRPC).Hands-on experience with vector databases and semantic search implementations.Experience with frameworks like Spring AI, LangChain4j, or equivalent Python-based orchestration (LangChain, LlamaIndex) with ability to bridge into Java services.Solid grasp of cloud platforms (AWS/Azure/Google Cloud Platform) — particularly AI/ML services (Bedrock, SageMaker, Azure OpenAI, Vertex AI).Experience with containerization and orchestration (Docker, Kubernetes).Strong database fundamentals — SQL (PostgreSQL/MySQL) and NoSQL (MongoDB, Redis).Familiarity with CI/CD pipelines, Infrastructure as Code (Terraform), and observability tooling (Prometheus, Grafana, ELK).Understanding of LLM concepts — tokenization, embeddings, fine-tuning vs. prompt engineering, context windows, function/tool calling.Excellent problem-solving skills with a track record of leading complex, high-scale engineering initiatives.Strong communication skills; experience working directly with cross-functional and leadership stakeholders.Nice to HaveExperience with Python for ML/AI prototyping alongside Java backend development.Exposure to agentic AI frameworks (multi-agent orchestration, tool-calling agents).Familiarity with MCP (Model Context Protocol) or similar AI integration standards.Prior experience in a technical lead or architect capacity.Contributions to open-source AI/Java tooling.Domain experience in [Finance/Healthcare/Retail/etc. — customize as needed].EducationBachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).