AI Engineering Manager

AI Engineering Manager

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.

We are looking for an AI Engineering Manager to lead the architecture, development, and delivery of Generative AI and Agentic AI solutions across the Microsoft Azure ecosystem.

This is a technical leadership role, not a traditional people-management position. The ideal candidate will have deep expertise in Azure AI Foundry, Microsoft Fabric, RAG, knowledge graphs, agentic workflows, AI agents, skills, and evaluation frameworks, combined with experience leading highly technical engineering teams.

The AI Engineering Manager will define technical direction, establish engineering standards, mentor senior engineers, and remain close enough to the technology to make and challenge key architecture decisions.

Key Responsibilities

• Define the technical strategy for Generative AI and Agentic AI solutions built primarily on Microsoft Azure.
• Lead the architecture and delivery of solutions using Azure AI Foundry and Microsoft Fabric.
• Define scalable patterns for agentic workflows, including agents, skills, tools, orchestration, memory, and enterprise system integration.
• Lead the design of RAG and knowledge-based AI architectures, including retrieval, chunking, embeddings, vector search, grounding, and knowledge graphs.
• Establish technical standards for building, testing, evaluating, and deploying AI applications.
• Define and oversee AI evaluation (evals) strategies to measure quality, accuracy, relevance, reliability, safety, and performance.
• Guide teams in selecting appropriate models, retrieval strategies, agent architectures, and AI technologies.
• Review technical designs and architecture decisions and provide hands-on technical guidance when needed.
• Lead the transition of AI solutions from experimentation and proof-of-concept stages into reliable production systems.
• Build and mentor a team of Senior AI Engineers and other technical specialists.
• Partner with Product, Data, Engineering, and business leadership to identify and prioritize high-value AI opportunities.
• Establish reusable frameworks, components, and engineering practices across AI initiatives.
• Manage technical risks, dependencies, scalability considerations, and delivery across multiple AI initiatives.
• Communicate complex AI architecture and technical tradeoffs clearly to both technical and non-technical stakeholders.
• Stay current with developments in agentic AI, LLMs, Azure AI, AI evaluation, knowledge graphs, and enterprise AI architectures.

• Deep hands-on experience with Azure AI Foundry — required.
• Strong experience designing and implementing Agentic AI / agentic workflows — required.
• Strong expertise in RAG architectures — required.
• Strong practical knowledge of graphs / knowledge graphs — required.
• Deep understanding of chunking, embeddings, retrieval, and vector search — required.
• Experience designing and implementing AI agents, skills, tools, and orchestration patterns — required.
• Experience with LLM / AI evaluation frameworks and methodologies — required.
• Strong experience with Microsoft Fabric or comparable Azure data platforms — strongly preferred.
• Proven experience leading highly technical AI or software engineering teams.
• Experience owning architecture and technical strategy for complex AI initiatives.
• Strong software engineering background, ideally with Python and cloud-native architectures.
• Experience taking AI solutions from experimentation through production at scale.
• Strong communication, stakeholder management, and technical leadership skills.

Nice to Have

• Experience in financial services, banking, lending,…