GoDigit - Technical Lead - AI Engineering

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.

(ref:hirist.tech)