Morningstar - Software Engineering Manager - Artificial Intelligence

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's 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.

OnshoreOffshore 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 to 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.