Java Full Stack Engineer ( AI Engineering)

Job summary

Design, build, and operate AI-enabled applications using LLMs, RAG, secure model integrations, and evaluation and monitoring practices. Develop Angular interfaces and scalable Java services, while collaborating with stakeholders and, at senior level, leading solution design, mentoring engineers, and driving delivery.

Job details

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.

What you’ll do

Design, build, and operate AI-enabled applications using LLMs, RAG, secure model integrations, and evaluation and monitoring practices. Develop Angular interfaces and scalable Java services, while collaborating with stakeholders and, at senior level, leading solution design, mentoring engineers, and driving delivery.

Requirements

Requires 5+ years of software engineering experience, including production or production-like AI application delivery, with strong Angular, TypeScript, Java, Spring Boot, distributed systems, and secure application design skills. Candidates should have practical LLM and RAG experience, use AI coding assistants responsibly, and bring CI/CD and DevOps expertise; Python, databases, cloud-native platforms, and senior-level leadership experience are also relevant.

Listed skills

• Angular · Preferred
• TypeScript · Preferred
• Java · Preferred
• Spring Boot · Preferred
• CI/CD · Preferred
• Docker · Preferred
• Kubernetes · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Angular
• TypeScript
• Java
• Spring Boot
• RESTful APIs
• Large Language Models
• Retrieval-Augmented Generation
• Embeddings
• Vector Search
• Prompt Design
• Structured Outputs
• AI Evaluation
• CI/CD
• Docker
• Kubernetes
• Python

Job areas

• Software
• Technology
• Engineering
• Data & Analytics
• Management & Leadership

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