Sr. Applied AI Engineer

Renesas Electronics

Lisbon, Portugal

About the role

We’re looking for an experienced AI Engineer to join our team working at the frontier of applied AI in Requirements Management and Hardware Engineering more in general.

This is a hands-on role where you’ll help build and evaluate real-world AI applications with immediate commercial impact. You’ll help design, develop, and deploy LLM-driven systems used by hardware product teams around the world, while learning how AI projects move from idea to production inside a product-led development team in the age of Agentic Hardware Engineering.

A day in the life of our AI Engineer

Develop agentic flows using off-the-shelf LLMs and applying modern harnessing methods (tool-calling, planning, skills, sub-agents, mcp servers, CLIs, etc.) to hardware design/requirement management use-cases;
Collaborate with software engineers, product managers, and designers in an agile, sprint-based environment to ship features and improvements;
Build evaluation pipelines, design metrics and gather data to measure and improve the performance of AI-driven systems;
Extend test-suite, refining and running benchmarks on our AI systems;
Benchmark models, prompts and approaches for speed, cost and accuracy and improve results methodically using techniques with highest impact (meta prompting, fine tuning, RAG, caching, prompt compression, distillation, etc.);
Participating in the full AI product lifecycle: from early-stage experimentation to deployment and continuous improvement.

Qualifications

Who We’re Looking For

Essential skills:
- Profound knowledge of LLM engineering and how LLM-based features are built and evaluated in production-ready environments;
- Advanced Python development skills to implement such systems;
- Production Experience with:
  - Agentic loops;
  - Tool-calling;
  - Agent orchestration;
  - MCP servers;
  - Evaluation and benchmarking pipelines;
  - Cost and latency optimization (context compression/model cascading etc.).
- Ability to plan experiments and execute tasks autonomously with an eye for detail;
- Quick learner to understand and keep up with the constantly evolving AI landscape;
- Experience in working in multi disciplinary teams to ship features to customers;
- Curiosity for user journeys and real-world use cases to validate solutions.
Nice to have:
- Production experience with:
  - Synthetic test data creation;
  - Distillation;
  - Agent Orchestration Debugging;
  - Finetuning models.
- Experience with (hardware) engineering software;
- Experience with developing end-to-end harnesses for agentic loops;
- Experience with building high concurrency asynchronous services;
- Experience with stateful agentic frameworks (like LangGraph).