About this role
Go Digit General Insurance Limited seeks a hands-on Technical Lead to guide AI engineers and deliver production-grade AI solutions. The position is on-site in Bengaluru, five days a week.
Responsibilities
- Lead AI initiatives from requirements analysis through development, testing, deployment and production support. Build scalable AI applications, APIs, microservices and reusable components using technologies including GenAI, LLMs, RAG, Agentic AI, MCP, computer vision, voice AI and document intelligence.
- Plan and track engineering work, resolve technical blockers and support timely delivery. Conduct technical and code reviews, mentor engineers, and contribute to sprint planning and releases.
- Maintain standards for security, reliability, maintainability, observability and scalability; promote reusable frameworks, tools and development practices.
Required qualifications
- At least 6 years of experience in software engineering, AI/ML engineering, GenAI or platform development; the listing also displays a 6–10-year experience range. Proven delivery of production-grade AI applications and experience leading engineers, reviewing code and mentoring team members.
- 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; and familiarity with Docker, Kubernetes, CI/CD, MLflow and observability tools.
- Strong problem-solving, technical communication and stakeholder-management skills. Structured posting metadata lists a bachelor's degree.
Preferred qualifications
- End-to-end delivery of enterprise AI solutions; knowledge of LLM evaluation, prompt engineering, guardrails and responsible AI; and experience with MLOps or LLMOps, model monitoring, versioning and automated deployment.
- Knowledge of AI security, data privacy, governance and regulatory compliance; optimization for accuracy, latency, scalability and cost; evaluation of emerging AI technologies; and establishment of reusable engineering standards.
Skills for this role
AI engineeringGenerative AILarge language modelsRAGAgentic AIMCPComputer visionVoice AIDocument intelligencePythonSQLAPIsMicroservicesDistributed systemsFastAPILangChainLangGraphSemantic KernelDockerKubernetesCI/CDMLflowObservabilityAI orchestrationCode reviewTechnical leadershipMentoringStakeholder managementLLM evaluationPrompt engineering