Technical Lead - AI Engineering

Company : Go Digit General Insurance Limited

Location : Bengaluru

Work Mode : On-site, five days a week

Role Overview :

We are seeking a hands-on Technical Lead to guide AI engineers and deliver production-grade AI solutions. The role combines technical leadership, active involvement in development, code reviews, deployment, mentoring, and production support.

Key Responsibilities :

- Lead AI initiatives from requirement analysis through production deployment.

- Build scalable AI applications, APIs, microservices, and reusable components.

- Develop solutions using GenAI, LLMs, RAG, Agentic AI, MCP, Computer Vision, Voice AI, and Document Intelligence.

- Plan and track engineering activities, resolve technical blockers, and ensure timely delivery.

- Conduct technical and code reviews while maintaining engineering standards.

- Mentor engineers and support sprint planning, testing, releases, and production issues.

- Ensure solutions are secure, reliable, maintainable, observable, and scalable.

- Drive the adoption of reusable frameworks, tools, and development practices.

Required Experience :

- 6+ years of experience in software engineering, AI/ML engineering, GenAI, or platform development.

- Proven experience delivering production-grade AI applications.

- Strong knowledge of LLMs, RAG, Agentic AI, MCP, and AI orchestration frameworks.

- Proficiency in Python, APIs, microservices, distributed systems, and SQL.

- Experience with FastAPI, LangChain, LangGraph, Semantic Kernel, or similar frameworks.

- Familiarity with Docker, Kubernetes, CI/CD, MLflow, and observability tools.

- Experience leading engineers, reviewing code, and mentoring team members.

- Strong problem-solving, technical communication, and stakeholder-management skills.

Preferred Experience :

- Experience leading end-to-end delivery of enterprise AI solutions.

- Understanding of LLM evaluation, prompt engineering, guardrails, and responsible AI practices.

- Experience with MLOps/LLMOps, model monitoring, versioning, and automated deployment.

- Knowledge of AI security, data privacy, governance, and regulatory compliance.

- Experience optimizing AI solutions for accuracy, latency, scalability, and cost.

- Ability to evaluate emerging AI technologies and guide their practical adoption.

- Experience establishing reusable engineering standards and best practices.