Java Full Stack Engineer ( AI Engineering)

Role overview

Responsibilities

• Develop secure RAG solutions using embeddings, vector search, metadata filtering, citations, and access controls.
• Integrate hosted models through secure APIs and implement prompts, structured outputs, tool calling, context management, and streaming.
• Test answer quality, groundedness, safety, latency, reliability, and cost; improve systems using telemetry and user feedback.
• Build data visualizations and interfaces for risk, metrics, policies, and controls.
• Design REST APIs and event-driven or microservices components with authentication and authorization.
• Apply code review, automated testing, CI/CD, observability, secure development, performance tuning, and production support.
• Collaborate with product, UX/UI, architecture, data, and business stakeholders to deliver measurable outcomes.
• Senior candidates may lead design, mentor engineers, influence standards, evaluate trade-offs, and drive cross-team delivery.

Skills and qualifications

• 5+ years of software engineering experience, including hands-on delivery of production or production-like AI-enabled applications.
• Strong Angular, TypeScript, Java, Spring Boot, REST API, distributed systems, and secure application design experience.
• Practical experience with LLM patterns, model APIs, RAG, embeddings, vector search, prompt design, structured outputs, tool calling, evaluation, observability, and AI security.
• Hands-on experience with Claude, GitHub Copilot, or comparable AI coding assistants, with disciplined review, testing, and security practices.
• Strong CI/CD and DevOps experience; Docker, Kubernetes, and cloud-native platforms are preferred.
• Experience with Python, SQL or NoSQL, data integration, caching, and data-intensive applications.
• Strong problem-solving, communication, and stakeholder-management skills; senior candidates should also bring architecture leadership, delivery ownership, and mentoring experience.