GoDigit - AI Engineering Manager

Company : Go Digit General Insurance Limited

Location : Bengaluru

Work mode : On-site, five days a week

About The Role We are looking for a senior individual contributor to drive architecture, solutioning, and engineering excellence across the AI organisation.

This is a horizontal engineering role that works across all AI teams. The role will define common technical standards, review solution designs and critical implementations, build reusable engineering patterns, and ensure AI systems are secure, scalable, reliable, and production-ready.

This role does not include people management, hiring, or primary delivery ownership.

Key Responsibilities

• Define and govern architecture and engineering standards across AI teams.
• Lead solutioning for complex, high-impact, and cross-team AI initiatives.
• Review solution architectures, technical designs, APIs, data flows, and integration patterns.
• Conduct critical code reviews and identify risks related to scalability, reliability, security, performance, and maintainability.
• Establish reference architectures and reusable patterns for Generative AI, RAG, agentic AI, MCP, machine learning, and multimodal AI.
• Define standards for AI evaluation, testing, prompt management, model selection, guardrails, observability, and cost optimisation.
• Standardise MLOps/LLMOps, deployment, versioning, monitoring, rollback, and incident-management practices.
• Build proof of concepts and reference implementations for new technologies and complex technical problems.
• Identify duplicated engineering efforts and drive the adoption of shared platforms and components.
• Support teams in resolving complex production issues and architectural bottlenecks.
• Evaluate emerging AI technologies and recommend practical adoption paths.
• Maintain architecture documentation, engineering guidelines, and technical decision records.
• Coach engineers and technical leads through design reviews and hands-on technical guidance.

Required Experience

• 7+ years of experience in software engineering, AI/ML, platform engineering, or solution architecture.
• Proven experience designing and reviewing production-grade AI systems.
• 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/LLMOps, and observability.
• Strong understanding of AI security, data privacy, responsible AI, reliability, and cost management.
• Ability to influence engineering teams through technical depth and sound architectural judgment.
• Strong problem-solving, documentation, and technical communication skills.

Preferred Experience

• 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 would be valuable.

(ref:hirist.tech)