Software Engineering Manager - AI

Manager – Software Engineering (AI), Offshore Delivery

Location

Mumbai , India

Role Summary

The Manager – Software Engineering (AI) will lead an offshore engineering team to design, build, and operate AI‑enabled software solutions in close collaboration with product, architecture, and business stakeholders. The role is responsible for end‑to‑end delivery (requirements to production), people leadership, and establishing robust engineering practices for AI and platform services supporting global customers.

Key Responsibilities

Delivery & Project Management

• Own end‑to‑end execution of AI and software engineering projects from offshore, including planning, estimation, staffing, execution, and risk management.
• Translate product and business requirements from onshore stakeholders into clear technical roadmaps, sprint plans, and deliverables for the offshore team.
• Ensure on‑time, on‑budget, and high‑quality delivery across workstream.
• Establish and track KPIs (velocity, quality, uptime, cost) and provide regular status reporting to onshore leadership.
  
  
  

Technical Leadership (AI & Platforms)

• Lead the design and implementation of AI‑enabled applications, Agents, services, and platforms (e.g., LLM‑based solutions, ML services, AI agents, automation workflows).
• Guide the team on architecture and technology choices, including microservices, distributed systems, model serving, and cloud‑native deployment patterns.
• Ensure robust engineering practices: code reviews, design reviews, automated testing, CI/CD, observability, and secure coding standards.
• Partner with data science / ML teams for model integration, inference optimization, and scalable deployment across environments (cloud, edge, internal platforms).
  
  
  

People Management & Coaching

• Manage, mentor, and grow a team of software engineers (and possibly ML/DevOps engineers), driving technical excellence, accountability, and ownership.
• Conduct regular 1:1s, performance reviews, and development plans; support career progression and skill upgrades in AI, cloud, and modern engineering practices.
• Foster a culture of transparency, continuous improvement, learning, and psychological safety across the offshore team.
  
  
  

Onshore–Offshore Collaboration

• Act as the primary offshore point of contact for onshore engineering managers, product owners, and business stakeholders.
• Align offshore delivery with onshore roadmaps, priorities, and quality standards; proactively manage dependencies and expectations.
• Enable effective overlap, communication rhythms (stand‑ups, reviews, planning), and documentation to ensure a “one‑team” operating model across time zones.
  
  
  

Governance, Quality & Risk

• Implement and enforce standards for architecture, coding, documentation, security, and compliance as defined by global technology leadership.
• Identify and manage delivery risks early (capacity, technical debt, dependencies), and drive mitigation plans with stakeholders.
• Ensure production readiness, operational stability, and effective incident response for systems owned by the offshore team.
  
  
  

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8–12 years of total software engineering experience, including 3+ years leading teams or managing projects.
• Strong hands‑on background in building scalable web or platform applications using modern back‑end languages and frameworks (e.g., Java, Python, Go, Node.js) and cloud platforms (e.g., AWS, Azure, GCP).
• Demonstrated experience delivering AI/ML or GenAI products (e.g., integrating models, AI agents, recommendation systems, NLP/LLM‑based features) into production systems.
• Proven track record of managing distributed/remote or offshore teams and executing projects in a global delivery model.
• Deep understanding of modern engineering practices: microservices, APIs, CI/CD, test automation, observability, and performance optimization.
• Excellent communication skills, with the ability to engage both technical and non‑technical stakeholders across regions.
  
  
  

Good To Have Experience

• M* authentication and authorization frameworks.
• Design and Build APIs and Integrate with LLMs
• Should have had experience in AI project in the last 1 yr , having delivered to production
  
  
  

Preferred Qualifications

• Experience building AI automation or developer productivity tools (e.g., AI agents, coding copilots, workflow automation).
  
  
  

Success Metrics

• Predictable delivery of roadmap commitments from offshore with high quality and minimal production incidents.
• Improvement in engineering productivity and cycle time (through automation, tooling, and process optimization).
• Growth and retention of a high‑performing offshore team with strong engagement scores.
• Positive feedback from onshore stakeholders on collaboration, communication, and business value delivered.
  
  
  

Morningstar is an equal opportunity employer.

Morningstars hybrid work environment gives you the opportunity to collaborate in-person each week as weve found that were at our best when were purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, youll have tools and resources to engage meaningfully with your global colleagues.

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