Tech Stack

Description

You will design, build, and deploy LLM-driven systems for requirements management and hardware engineering, developing agentic flows and evaluation pipelines. Collaborate with a cross-functional team in an agile environment to ship features with immediate commercial impact.

Requirements

• Profound knowledge of LLM engineering and how LLM-based features are built and evaluated in production-ready environments
• Advanced Python development skills
• Production experience with: agentic loops, tool-calling, agent orchestration, MCP servers, evaluation and benchmarking pipelines, cost and latency optimization
• Ability to plan experiments and execute tasks autonomously with an eye for detail
• Quick learner to keep up with the evolving AI landscape
• Experience working in multidisciplinary teams to ship features to customers
• Curiosity for user journeys and real-world use cases

Responsibilities

• Develop agentic flows using off-the-shelf LLMs and modern harnessing methods for hardware design/requirement management use-cases
• Collaborate with software engineers, product managers, and designers in an agile, sprint-based environment
• Build evaluation pipelines, design metrics, and gather data to measure and improve AI system performance
• Extend test-suite, refine and run benchmarks on AI systems
• Benchmark models, prompts and approaches for speed, cost and accuracy; improve results using techniques like meta prompting, fine tuning, RAG, caching, prompt compression, distillation
• Participate in the full AI product lifecycle from experimentation to deployment and continuous improvement