AI Engineering Manager

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

📋 Description

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

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

• Create scalable patterns for agentic workflows, encompassing agents, skills, tools, orchestration, memory, and enterprise system integration.

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

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

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

• Assist teams in choosing models, retrieval strategies, agent architectures, and AI technologies.

• Evaluate technical designs and architectural decisions, providing hands-on technical guidance as necessary.

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

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

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

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

• Manage technical risks, dependencies, scalability considerations, and delivery across multiple AI initiatives.

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

• Stay updated on agentic AI, LLMs, Azure AI, AI evaluation, knowledge graphs, and enterprise AI architectures.

⛳️ Requirements

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

• Extensive experience in designing and implementing Agentic AI and agentic workflows — required.

• Strong expertise in RAG architectures — required.

• In-depth practical knowledge of graphs and knowledge graphs — required.

• Profound 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 track record of leading 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 in progressing AI solutions from experimental phases to large-scale production.

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

• Experience 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 in AI governance, observability, responsible AI, and security — nice to have.

• Experience in establishing AI engineering standards and evaluation frameworks across 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 paths.

• Study plans, courses, and additional certifications tailored to the role.

• Access to Udemy Business.

• English lessons.

• Travel opportunities to industry conferences and client meetings.

• Career development plans and mentorship programs.

• Special day rewards for birthdays, work anniversaries, and other personal milestones.

• Company-provided equipment.

• Flexible working options.

• Additional benefits may vary based on location in LATAM.