AI Engineering Lead

What is this position about?

• Lead end-to-end project delivery with clear governance and strong stakeholder communication
• Mentor junior engineers and contribute to proposals and new business initiatives
• Define what AI systems should and should not attempt, and communicate risks and tradeoffs transparently to clients
• Design and build RAG systems, agentic frameworks, and LLM-powered solutions robust enough for production
• Apply advanced prompt engineering techniques, including instruction design, few-shot sets, structured outputs, and tool/agent prompts
• Lead feasibility assessments to select the right approach among prompting, RAG, fine-tuning, or classical ML
• Design evaluation frameworks, including LLM-as-a-judge methods, custom metrics (recall@k, precision@k), and go/no-go gates
• Run structured experiments across prompts, retrievers, chunking strategies, and models, grounded in evidence rather than intuition
• Identify and categorize model failure modes, including hallucinations, retrieval misses, and instruction-following errors
• Build scalable inference infrastructure and CI/CD pipelines for AI/ML models
• Automate the full MLOps/LLMOps lifecycle, including tracking, versioning, deployment, monitoring, and retraining
• Design APIs, microservices, and orchestration layers optimized for latency, cost, and reliability
• Expert-level Python, strong Git practices, and experience with ML/LLM versioning
• Solid cloud experience across AWS, Azure, or GCP (Azure preferred), plus containerization and orchestration
• Hands-on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation
• Proven MLOps/LLMOps track record using tools such as MLflow, Weights & Biases, or similar
• Practical evaluation design skills, including metrics, dataset curation, and structured experimentation
• Experience with event-driven architectures, APIs, and microservices
• Strong communication skills, equally comfortable engaging engineering teams and senior stakeholders
• Preferred: experience with the Databricks MLOps platform, LLM fine-tuning, building agentic GenAI systems, Infrastructure as Code, security and observability for AI services, a classical ML background, and open-source contributions

• What about languages?
• English: Advanced (required for effective communication with global teams)
• How much experience must I have?
• 6+ years of experience building and deploying AI solutions in production environments, with a strong track record across RAG, agentic systems, and MLOps/LLMOps.

Our Perks and Benefits

Every day lunches! (headquarters)

• Vegetarian, vegan, gluten and sugar free options.
• Gourmet meals every Friday with our on-site chef!

• ⚖️ Flexible working options to help you strike the right balance.
• 💻 All the equipment you need to harness your talent (Macbook and accessories).
• 🍎 Snacks and beverages available everyday (headquarters).
• 🎉 After office events, football, tennis and game nights (headquarters).
• ⚽ Everyone is welcome to join our football league every Wednesday's and Friday's.
• 🎱 Challenge your teammates to a pool game and win the office's trophy!
• 🎾 Tennis courts available for friendly matches.
• 🎮 Not a sports person? Don't worry, we also have chess championships, game and music nights for you to join!

📚 Learning opportunities

• AWS Certifications (we are AWS Partners).
• Study plans, courses and other certifications.
• English Lessons.
• Learn from your teammates on our Tech Tuesdays!

• 🧭 Mentoring and Development opportunities to shape your career path.
• 🎁 Anniversary and birthday gifts.
• 📍 Great location and even greater teammates!
• So what are the next steps?
• Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we'll explore working together!