07 Nov
|
SBI General Insurance
|
Thane
07 Nov
SBI General Insurance
Thane
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 deliveryideally 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:
- Robust 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.
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