AI Engineering Lead

AI Engineering Lead Full-time Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com We are seeking an AI Engineering Lead to contribute to our next level of growth and expansion. Job Description 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 Qualifications 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. Additional Information 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