Senior AI Engineer

⭐ Role Overview

We are seeking a Senior AI Engineer specializing in LLMs to lead the design, evaluation, and deployment of production-grade generative AI systems. In this role, you will own end-to-end LLM solutions, from prototyping to scalable production, while establishing best practices in evaluation, reliability, and responsible AI.

⭐ How will you make an impact?

• Lead the design and development of LLM-powered applications (chatbots, copilots, agents, internal tools).

• Own and evolve the LLM evaluation (evals) strategy, including designing gold-standard datasets and benchmarks, building automated eval pipelines and scoring systems and defining metrics for factuality, grounding, robustness, and user impact.

• Diagnose and resolve complex failure modes (hallucinations, retrieval issues, agent breakdowns).

• Optimize systems for latency, cost, scalability, and reliability in production.

• Mentor junior engineers and guide best practices in LLM development and evaluation.

• Collaborate cross-functionally with product, data, and leadership to shape AI strategy.

• Set standards for responsible AI, including safety, bias mitigation, and observability.

⭐ What makes you a great fit?

• 5+ years of experience in software engineering, machine learning, and applied AI with a track record of driving projects to completion.

• Strong software engineering fundamentals (testing, modular design, dependency injection) in Python.

• A track record of taking AI and LLM-powered features from initial concept through deployment and long-term production maintenance.

• Experience implementing automated testing strategies for non-deterministic systems, and strong debugging and analytical skills for ambiguous model behavior.

• A strong understanding of prompt engineering and prompt lifecycle management, RAG architectures and retrieval evaluation, and LLM limitations and failure patterns.

• Solid experience in using Data Analytics techniques (SQL, analysis and visualizations) to inform Product decisions and delivery.

• A heavy product mindset to deeply understand our product and our customer needs to design the right solutions for them.

• Strong tech leadership and mentorship skills, and the ability to independently drive projects to completion.

• Clear communication of trade-offs, risks, and system performance to stakeholders.

⭐ How can you earn extra bonus points?

• Proven experience driving ambiguous projects to completion, mentoring teams, and communicating complex technical risks to stakeholders.

• The ability to design robust, production-grade evaluation at scale using advanced metrics and statistical validation.

• Deep expertise in model fine-tuning, adversarial red-teaming, and safety testing to protect the system from edge-case vulnerabilities.