AI Engineering Manager (India)

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.