Java Full Stack Engineer ( AI Engineering)

What you will do:

• Design, build, and operate AI-driven applications that use LLMs for natural-language interaction, intelligent search, summarization, content generation, and workflow automation.
• Develop retrieval-augmented generation (RAG) solutions that securely connect models to enterprise data using embeddings, vector search, metadata filtering, citations, and access controls.
• Integrate commercial or internally hosted models through secure APIs and implement prompt management, structured outputs, tool or function calling, context management, and streaming responses.
• Create evaluation datasets and automated tests for answer quality, groundedness, safety, latency, reliability, and cost; use production telemetry and user feedback to improve the system.
• Build intuitive Angular interfaces and data visualizations that allow users to search, filter, review, and interact with risk, metric, policy, and control information.
• Design scalable Java and Spring Boot services, RESTful APIs, and event-driven or microservices-based components with appropriate authentication and authorization.
• Use Claude, GitHub Copilot, and similar AI engineering tools responsibly for code exploration, implementation, refactoring, test generation, debugging, review, and documentation while independently validating generated output.
• Apply software engineering best practices, including code review, automated testing, CI/CD, observability, secure development, performance tuning, and production support.
• Partner with product managers, UX/UI teams, architects, data specialists, and business stakeholders to identify high-value use cases and translate requirements into measurable technical outcomes.
• For senior candidates, lead solution design, mentor engineers, influence standards, assess trade-offs across model quality, latency, cost, security, and maintainability, and drive delivery across teams.

Skills & Qualifications:

• 5+ years of software engineering experience, including hands-on delivery of production or production-like AI-enabled applications.
• Primary skills: Strong full-stack development experience with Angular and TypeScript, Java and Spring Boot, RESTful APIs, distributed systems, and secure application design.
• Practical experience with LLM application patterns, model APIs, RAG, embeddings, vector search, prompt design, structured outputs, tool calling, evaluation, observability, and AI security.
• Hands-on use of Claude, GitHub Copilot, or comparable AI coding assistants, with disciplined review, testing, and security practices.
• Strong CI/CD and DevOps experience covering automated builds, testing, code-quality and security checks, deployment, release controls, and production monitoring; familiarity with Docker, Kubernetes, and cloud-native platforms is preferred.
• Experience with Python, SQL or NoSQL databases, data integration, caching, and data-intensive applications.
• Strong problem-solving, communication, and stakeholder-management skills; senior candidates should also demonstrate architecture leadership, delivery ownership, and mentoring experience.