AI Engineering Manager (India)

About the Role

Midera Food Processing, Inc. is building a global enterprise AI capability. The AI Engineering Manager (India) will lead the technical delivery and development team supporting this transformation. This is a critical leadership role within Midera's developing AI organization. The manager will build and manage the India-based AI engineering team while staying deeply involved in architecture, development, code review, technical design, and solution delivery. The role works closely with the U.S.-based Manager, Enterprise AI and follows a hybrid schedule (3 days per week in the Bengaluru office) with periodic U.S. Central Time overlap.

Responsibilities

• AI Engineering Team Leadership: Recruit, interview, hire, onboard, and develop AI engineers; manage performance, career development, workload, priorities, and delivery expectations; build a strong engineering culture focused on quality, accountability, collaboration, documentation, and continuous improvement.
• Hands-On AI Engineering: Contribute to high-priority AI applications and integrations; review code, pull requests, technical designs, and architecture; troubleshoot complex technical and production issues; build prototypes and proof-of-concept solutions; establish coding and engineering standards.
• AI Solution Architecture: Design enterprise-grade AI applications, agents, copilots, intelligent workflows, and automation solutions; establish reusable architecture patterns; lead technical design for solutions involving LLMs, generative AI, RAG, enterprise search, APIs, and workflow automation.
• Microsoft AI Platform: Lead implementation involving Microsoft Copilot, Copilot Studio, Azure AI services, Azure OpenAI, Microsoft Fabric, Power Platform, Power Automate, Microsoft Graph, and Azure cloud services; establish standards for secure interaction between Copilot, agents, data, and business systems.
• Data & Microsoft Fabric Integration: Partner with Data & Analytics to design the relationship between Microsoft Fabric and AI applications; ensure AI solutions consume trusted, governed enterprise data; collaborate on data access patterns, semantic models, vector databases, and AI-ready datasets.
• Enterprise AI Development: Lead development of AI solutions across procurement, supply-chain intelligence, aftermarket service, quote assistance, engineering knowledge, product documentation, sales and customer intelligence, CRM, field service, ERP workflows, financial analytics, internal knowledge assistants, document processing, workflow automation, software-development productivity, and manufacturing processes.
• Integration with Enterprise Applications: Develop secure API-based integration patterns with ERP, CRM, field service, Microsoft Dynamics 365, and other platforms; ensure alignment with Midera’s enterprise architecture.
• AI Development Standards & Lifecycle: Establish disciplined lifecycle covering requirements, design, architecture review, source control, CI/CD, automated testing, security review, UAT, deployment, monitoring, documentation, support, and continuous improvement; promote DevOps, MLOps, and LLMOps practices.
• AI Quality & Production Readiness: Define testing methodologies for AI-generated outputs; implement human review processes; set up logging, monitoring, auditing, and observability; monitor solution quality, performance, availability, usage, and cost.
• Governance, Security & Responsible AI: Translate AI governance requirements into technical controls; ensure compliance with cybersecurity, privacy, data-management, and responsible AI standards; establish authentication, authorization, data access, prompt security, and production deployment controls.
• Consultant & Partner Management: Work with Microsoft and external AI consulting partners; review partner architectures and code; ensure knowledge transfer and reduce dependence on outside consultants.
• Global Collaboration: Partner with U.S. leadership and divisional IT teams across multiple countries; translate technical topics into clear business language; participate in AI discovery and solution-design sessions with stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, Engineering, or related discipline, or equivalent professional experience.
• Approximately 10+ years of professional software engineering, cloud engineering, data engineering, AI/ML, or related technical experience.
• Demonstrated experience managing or technically leading software engineering teams, including recruiting, interviewing, developing, and managing engineers.
• Strong hands-on software development experience with Python.
• Experience designing and delivering production-grade enterprise applications.
• Demonstrated experience developing generative AI or LLM-based applications.
• Deep understanding of Large Language Models, Retrieval-Augmented Generation (RAG) architectures, embeddings, vector search, AI agents, tool/function calling, prompt design, and enterprise AI architecture.
• Experience integrating applications with APIs, databases, cloud platforms, and enterprise applications.
• Strong knowledge of software architecture, engineering principles, authentication, authorization, APIs, security, source control, and CI/CD.
• Experience performing code reviews and technical design reviews.
• Ability to troubleshoot complex technical problems and take solutions from idea through production deployment.
• Exceptional English communication skills - fluent spoken and written, strong presentation ability, and capability to lead technical discussions with U.S. and global teams.

Preferred Qualifications

• Experience with Microsoft Copilot Studio, Microsoft Copilot, Azure AI, Azure OpenAI, Microsoft Fabric, Microsoft Power Platform, Power Automate, Microsoft Graph, or Microsoft Azure.