GoDigit - AI Engineering Manager

Go Digit General Insurance Limited seeks a senior individual contributor to lead architecture, solution design and engineering standards across its AI teams. The role is on-site in Bengaluru, five days a week. Despite the manager title, it does not include people management, hiring or primary delivery ownership.

Responsibilities

• Define common architecture and engineering standards; lead solution design for complex, high-impact initiatives spanning AI teams. Review architectures, APIs, data flows, integrations and critical code for scalability, reliability, security, performance and maintainability.
• Develop reference architectures and reusable patterns for generative AI, RAG, agentic AI, MCP, machine learning and multimodal AI. Set standards for evaluation, testing, prompt management, model selection, guardrails, observability and cost optimisation.
• Standardise MLOps and LLMOps practices covering deployment, versioning, monitoring, rollback and incident management. Build proofs of concept and reference implementations, promote shared components, help resolve production issues and architectural bottlenecks, and assess emerging AI technologies.
• Maintain architecture documentation, engineering guidelines and technical decision records. Coach engineers and technical leads through design reviews and hands-on guidance.

Required qualifications

• At least 7 years of experience in software engineering, AI/ML, platform engineering or solution architecture, with proven experience designing and reviewing production-grade AI systems. The posting's structured data lists a bachelor's degree.
• Strong knowledge of LLMs, RAG, agentic systems, MCP, machine learning and AI evaluation; advanced experience with Python, APIs, microservices, distributed systems, event-driven architecture and SQL.
• Experience with cloud AI services, containers, Kubernetes, CI/CD, MLOps or LLMOps, and observability. Understanding of AI security, data privacy, responsible AI, reliability and cost management, plus sound architectural judgment, problem-solving, documentation and technical communication skills.

Preferred

Experience building enterprise AI platforms or shared engineering capabilities in insurance, financial services or another regulated industry. Exposure to large-scale AI governance, platform modernisation and emerging-technology evaluation is valuable.