AI Engineering Manager

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Formulate the technical strategy for Generative AI and Agentic AI solutions primarily utilizing Microsoft Azure.

• Oversee the architecture and implementation of solutions leveraging Azure AI Foundry and Microsoft Fabric.

• Establish scalable frameworks for agentic workflows, encompassing agents, skills, tools, orchestration, memory, and integration with enterprise systems.

• Direct the design of Retrieval-Augmented Generation (RAG) and knowledge-based AI architectures, which include retrieval, chunking, embeddings, vector search, grounding, and knowledge graphs.

• Set technical standards for the development, testing, assessment, and deployment of AI applications.

• Define and manage AI evaluation strategies to assess quality, accuracy, relevance, reliability, safety, and performance.

• Advise teams on selecting suitable models, retrieval methods, agent architectures, and AI technologies.

• Evaluate technical designs and architectural choices, providing hands-on technical support as required.

• Lead the transition of AI solutions from experimental and proof-of-concept phases to robust production systems.

• Build and mentor a team of Senior AI Engineers and other technical experts.

• Collaborate with Product, Data, Engineering, and business leadership to recognize and prioritize high-impact AI opportunities.

• Create reusable frameworks, components, and engineering practices across AI projects.

• Manage technical risks, dependencies, scalability concerns, and delivery across multiple AI projects.

• Clearly communicate complex AI architecture and technical trade-offs to both technical and non-technical stakeholders.

• Keep abreast of advancements in agentic AI, large language models (LLMs), Azure AI, AI evaluation, knowledge graphs, and enterprise AI architectures.

⛳️ Requirements

• Extensive hands-on experience with Azure AI Foundry — required.

• Strong background in designing and implementing Agentic AI and agentic workflows — required.

• Profound expertise in RAG architectures — required.

• Solid practical knowledge of graphs and knowledge graphs — required.

• In-depth understanding of chunking, embeddings, retrieval, and vector search — required.

• Experience in designing and implementing AI agents, skills, tools, and orchestration patterns — required.

• Familiarity with LLM and AI evaluation frameworks and methodologies — required.

• Strong experience with Microsoft Fabric or similar Azure data platforms — strongly preferred.

• Proven ability to lead highly technical AI or software engineering teams.

• Experience in owning architecture and technical strategy for complex AI projects.

• Strong software engineering background, preferably with Python and cloud-native architectures.

• Experience transitioning AI solutions from experimentation to large-scale production.

• Excellent communication, stakeholder management, and technical leadership abilities.

• Background in financial services, banking, lending, insurance, or related sectors — nice to have.

• Experience with enterprise-scale AI implementations — nice to have.

• Familiarity with multi-agent systems and advanced orchestration patterns — nice to have.

• Knowledge of AI governance, observability, responsible AI, and security practices — nice to have.

• Experience in establishing AI engineering standards and evaluation frameworks throughout an organization — nice to have.

• Familiarity with Azure DevOps, CI/CD, and cloud infrastructure — nice to have.

🏝️ Benefits

• Certifications in AWS, Databricks, and Snowflake.

• Access to AI learning pathways.

• Customized study plans, courses, and additional certifications relevant to the role.

• Access to Udemy Business.

• English language lessons.

• Opportunities for travel to participate in industry conferences and meet clients.

• Career development plans and mentorship initiatives.

• Recognition rewards for birthdays, work anniversaries, and other significant personal milestones.

• Company-provided equipment.

• Flexible working arrangements.

• Additional benefits may vary based on your location in LATAM.