
We are looking for a highly experienced and technically strong AI Engineering Manager to lead and mentor a team of Machine Learning and AI Engineers. This role will drive the execution, delivery, and operational excellence of enterprise AI/ML products and platforms within the Life Insurance and Financial Services sector.
The role operates primarily in a GCP cloud environment and requires bridging architectural design with hands-on engineering execution. The candidate will manage engineering workloads, guide technical decisions, ensure high code quality, and drive project timelines for enterprise-grade AI solutions.
Key Responsibilities
Team Leadership & Project Management
- Own end-to-end delivery of AI/ML projects including sprint planning, backlog grooming, workload management, and resource allocation.
- Provide technical guidance and mentorship to AI/ML engineers, including code reviews and best practices for MLOps, software engineering, and cloud infrastructure.
- Act as the primary technical point of contact for product managers, architects, and business stakeholders.
- Define and enforce engineering standards for development, testing, CI/CD, and monitoring of AI services.
- Recruit, onboard, mentor, and conduct performance reviews for the AI engineering team.
- Collaborate with Data Engineering, DevOps, and other teams to integrate AI models into enterprise systems and data pipelines.
- Identify and manage technical risks, dependencies, and delivery blockers to maintain project velocity.
Technical Delivery
- Implement and operationalize MLOps pipelines for model training, versioning, deployment, monitoring, and explainability.
- Guide teams in leveraging AI platform capabilities such as RAG pipelines, LLM gateways, and vector databases to build business use cases.
- Ensure security, scalability, and performance of production AI services and underlying cloud infrastructure.
Must-Have Skills & Requirements
- 8+ years of experience in Software Engineering, Machine Learning Engineering, or Data Science.
- Minimum 3+ years in a team management or leadership role.
- Proven experience managing and mentoring engineering teams.
- Strong experience with project management methodologies (Scrum/Kanban) and tools such as Jira.
- Hands-on experience with production-scale MLOps and GenAIOps implementations.
- Deep expertise in cloud platforms, preferably GCP.
- Strong understanding of modern data architecture including vector databases, data warehousing, and ETL/ELT pipelines.
- Solid software engineering fundamentals including API design, system architecture, Git, and CI/CD or DevSecOps pipelines.
- Experience with GenAI technologies such as LLM orchestration frameworks, prompt engineering, and RAG architectures.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Good-to-Have / Preferred Skills
- Experience managing distributed or multi-geographical engineering teams.
- Knowledge of regulatory requirements within the BFSI or insurance domain (data privacy, Responsible AI).
- Azure cloud or multi-cloud project experience.
- Experience with streaming data platforms and real-time AI processing.
- Cloud certifications such as GCP Professional Cloud Architect or ML Engineer.

About Quantiphi
About
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine and realize transformational opportunities at the heart of the business. Since its inception in 2013, Quantiphi has solved the toughest and most complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve accelerated and quantifiable business results.
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Bengaluru, Mumbai, and Trivandrum
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