AI Engineering Manager

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

Job Description

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.

Qualifications

• 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, insurance, or related industries.
• Experience with enterprise-scale AI implementations.
• Experience with multi-agent systems and advanced orchestration patterns.
• Experience with AI governance, observability, responsible AI, and security.
• Experience establishing AI engineering standards and evaluation frameworks across an organization.
• Experience with Azure DevOps, CI/CD, and cloud infrastructure.

Additional Information

Our perks and benefits:

📚 Learning Opportunities:

• Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
• Access to AI learning paths to stay up to date with the latest technologies.
• Study plans, courses, and additional certifications tailored to your role.
• Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
• English lessons to support your professional communication.

👨🏽‍💻 Travel opportunities to attend industry conferences and meet clients.

👩‍🏫 Mentoring and Development:

• Career development plans and mentorship programs to help shape your path.

🎁 Celebrations & Support:

• Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
• Company-provided equipment.

⚖️ Flexible working options to help you strike the right balance.

Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.