Team Lead Digital Innovations

SBI General Insurance; Thane; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

SBI General Insurance seeks a Team Lead AI Projects to drive delivery, management, and strategic execution of AI initiatives. You will lead engineers, oversee vendor evaluation, and align AI efforts with business goals while guiding architecture decisions.

The role emphasizes leadership and project execution over hands‑on model development, with a focus on insurance applications such as claims processing, fraud analytics, and underwriting automation.

Qualifications

• 7–10 years in software engineering and technology project management with 2+ years in a leadership role.
• Strong foundation in software engineering, architecture, microservices, and SDLC.
• Proven Agile/Scrum experience with Jira, Confluence, and Asana.
• Vendor and partner management experience, with SLAs and external deliverables.
• Solid AI literacy: ML workflows, NLP, computer vision, and generative AI concepts.
• Cloud familiarity with AWS/Azure/GCP and API integrations.
• Insurance domain knowledge is a plus; PM certifications are beneficial.

Responsibilities

• Drive end-to-end management of AI projects, defining scope, milestones, and delivery schedules.
• Implement Agile/Scrum, sprint planning, stand-ups, backlog grooming, and retrospectives.
• Translate business requirements into technical roadmaps and actionable user stories.
• Monitor KPIs, budget, and technical risk across multiple AI initiatives.
• Lead evaluation and onboarding of third-party AI vendors and tools.
• Mentor a team of 3–4 engineers, ensuring code quality and architectural alignment.
• Oversee integration between vendor solutions and internal microservices in insurance context.

Skills

Team leadership

Agile/Scrum

Project management

Software architecture

AI/ML literacy

Vendor management

Communication

Cloud platforms

Tools

Jira

Confluence

Asana

Job description

We are looking for a technically grounded Team Lead AI Projects to drive the delivery, management, and strategic execution of artificial intelligence solutions.

In this role, you will lead a team of engineers and oversee AI initiatives, serving as the bridge between technical teams, external vendors, and business leadership. Coming from a solid software engineering background, you will leverage strong project management practices to define project roadmaps, manage resource allocation, evaluate third‑party AI tools/vendors, and ensure seamless delivery ideally within the insurance domain. While this role focuses on leadership, vendor oversight, and project execution rather than hands‑on AI model development, technical literacy in AI concepts is essential to guide architectural decisions and assess vendor capabilities.

Role & responsibilities

Project Management & Execution

• Drive end-to-end management of AI projects, defining project scope, milestones, resource planning, risk management, and delivery schedules.
• Implement Agile/Scrum methodologies, facilitating sprint planning, daily stand‑ups, backlog grooming, and retrospective meetings.
• Work closely with Product Managers and Business Stakeholders to translate complex business requirements into clear technical roadmaps and actionable user stories.
• Monitor project health, KPIs, budget allocation, and technical risk across multiple concurrent AI initiatives.

Vendor Evaluation & Management

• Lead the evaluation, selection, and onboarding of third‑party AI vendors, SaaS platforms, external tools, and service providers.
• Conduct technical due diligence, benchmark third‑party AI tools/models, and assess vendor capabilities against internal security, performance, and scalability standards.
• Manage vendor relationships, service‑level agreements (SLAs), contracts, deliverables, and performance reviews to ensure high‑quality delivery on time and within budget.

Technical Leadership & Team Guidance

• Lead and mentor a team of 3/4 software and AI engineers, fostering a high‑performance culture focused on engineering quality and continuous learning.
• Oversee system integration and architectural alignment between vendor solutions, internal microservices, and core enterprise software.
• Ensure high standards for code review, integration practices, system stability, and compliance.

Domain Application (Insurance Preferred)

• Apply AI application management to address core insurance industry challenges, such as automated claims processing, fraud detection, risk assessment, underwriting automation, and conversational AI.

Required Qualifications & Experience

• Experience: 7 to 10 years of professional experience in software engineering and technology project management, with at least 2+ years in a team leadership or technical project lead role.
• Development Background: Strong foundation in core software engineering principles, system architecture, microservices, and software development lifecycle (SDLC).
• Project Management Skills: Proven track record in Agile/Scrum methodologies, risk mitigation, sprint delivery, and project management tools (e.g., Jira, Confluence, Asana).
• Vendor & Partner Management: Demonstrated experience evaluating RFP responses, conducting third‑party tool assessments, negotiating SLAs, and managing external vendor deliverables.

Conceptual AI/ML Literacy

• Strong conceptual understanding of Machine Learning workflows, Deep Learning capabilities, NLP, Computer Vision, and Generative AI/LLMs.
• Ability to evaluate AI/ML model architectures, APIs, and MLOps deployment pipelines from a high‑level design perspective.

Cloud & Infrastructure

• Understanding of cloud platform architectures (AWS, Azure, or GCP) and API‑driven integrations.

Preferred Qualifications

• Insurance Industry Knowledge: Familiarity with insurance domain concepts (Claims, Underwriting, Policy Administration, Fraud Analytics, Actuarial processes) and industry compliance/data privacy standards.
• Project management certification (e.g., PMP, CSM, or Agile PM) is a plus.

Key Soft Skills

• Strong vendor negotiation and relationship‑building capabilities.
• Clear communication skills with the ability to articulate technical AI trade‑offs to business executives.
• Exceptional organizational, time‑management, and problem‑solving abilities.