AI Engineering Manager

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Blend360

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🏥 Healthcare

🏨 Hospitality

✈️ Travel

💰 $100M Private Equity Round on 2022-08

Healthcare • Hospitality • Travel

Blend360 is a professional services company specializing in AI, data analytics, and data-driven solutions. They work with Fortune 1000 and large enterprise brands to tackle significant challenges by integrating people and artificial intelligence. Blend360 focuses on several domains including business intelligence, data engineering, data science, MLOps, and data governance. Their industries of expertise encompass financial services, energy, healthcare and life sciences, retail, technology, media & telecom, and travel & hospitality. Blend360 is recognized for their AI and data solutions, having earned accolades such as "AI-Enabling Solution of the Year" and being listed among the "Top Generative AI Service Providers 2024.

📋 Description

• 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 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 technical and non-technical stakeholders • Stay current with developments in agentic AI, LLMs, Azure AI, AI evaluation, knowledge graphs, and enterprise AI architectures

🎯 Requirements

• Deep hands-on experience with Azure AI Foundry — required • Strong experience designing and implementing Agentic AI and agentic workflows — required • Strong expertise in RAG architectures — required • Strong practical knowledge of graphs and 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 and 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 • Experience in financial services, banking, lending, insurance, or related industries — nice to have • Experience with enterprise-scale AI implementations — nice to have • Experience with multi-agent systems and advanced orchestration patterns — nice to have • Experience with AI governance, observability, responsible AI, and security — nice to have • Experience establishing AI engineering standards and evaluation frameworks across an organization — nice to have • Experience 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 attend industry conferences and meet clients • Career development plans and mentorship programs • Special day rewards for birthdays, work anniversaries, and other personal milestones • Company-provided equipment • Flexible working options • Other benefits may vary according to your location in LATAM