Senior Engineer AI Specialist

At Mindera, we believe that software is built by people, for people, with high-performance systems that impact users worldwide. We are looking for a Senior Engineer AI Specialist to join an agile, collaborative team where your voice matters as much as your code. As a Senior AI Engineer you'll be part of the development of our next-generation autonomous AI agents and intelligent workflows. In this role, you will design, build, and deploy production-grade agentic architectures, bridging advanced LLM reasoning with existing enterprise backends. You will be instrumental in building Model Context Protocol (MCP) servers, crafting custom sub-agent ecosystems, and integrating advanced RAG and memory pipelines into robust Java-based applications. We value empathy, self-organization, and a positive attitude. If you are approachable, communicate clearly, and believe that team fit is just as important as technical expertise, you'll feel right at home here. At Mindera, we encourage the use of AI to assist with coding and related tasks. We find that a person's engineering and software craft skills have a big impact on long-term successful delivery, with or without AI. Our goal in the interview process is to understand the candidate’s knowledge and skills in engineering. If you need to, or plan to use AI, please be transparent with us when you're using it, to avoid issues and misunderstandings that can either impact your chance of securing the role or impact your success at Mindera. When you join Mindera we welcome you into a fun and politics-free work culture , built on the principles of lean and self-organisation. Note: Depending on the project and our clients' needs, you may get the chance to pack your bags and take off every now and then. Typically, we estimate travel time to be between 0% and 15%. At Mindera, we thrive on solving complex engineering challenges and driving technological innovation. As a Senior Engineer AI Specialist , you will focus on: Backend & AI Integration: Build scalable microservices using Java 17/21+ and Spring Boot, integrating commercial LLMs (e.g., Azure OpenAI Service, Anthropic Claude, OpenAI) via Spring AI. Agentic Systems: Architect autonomous, multi-agent workflows using one or more of LangGraph, LangChain4j, or CrewAI, for dynamic, multi-step reasoning. Context & Memory: Develop MCP (Model Context Protocol) servers, work with vector databases, and build RAG pipelines for efficient, persistent data retrieval. Prompting & Skills: Create and version-control custom AI "skills" and complex prompts (e.g., using .md files) for safe, deterministic outputs. Enterprise Reliability: Implement AI guardrails, rate limiting, fallbacks, and observability/tracing for secure, production-grade performance. Collaboration: Partner with App Engineers, Product, and Data teams to deliver seamless end-to-end AI experiences on Mobile and Web. Requirements Key Qualifications: Experience: 7+ years of professional…