InsuranceDekho is building an AI Lab to reimagine insurance using agentic systems that can reason, decide, and execute across the value chain. We are looking for an Engineering Manager who is both a strong builder and a pragmatic leader someone who can go from 0?1 while scaling systems and teams.
You will own full-stack architecture across AI, backend, and frontend systems, with Python-led backend and AI systems forming the core of the stack.
What You Will Own
Build and ship 0?1 AI-powered products impacting revenue and operations
Own architecture across AI systems, Python backend services, APIs, and frontend applications
Drive Python-first backend development for AI orchestration, data pipelines, and high-scale services
Design scalable, low-latency APIs and microservices powering AI-driven workflows
Translate ambiguous business problems into production-grade systems
Drive fast iteration cycles: prototype ? validate ? productionize
Hire, mentor, and raise the bar for a high-caliber engineering team
Establish strong engineering practices across backend, frontend, and ML systems
Partner closely with product and business to define roadmap and execution
What Were Looking For
8 to 12+ years of experience building and scaling backend-heavy systems
Strong expertise in Python (must-have) as a primary backend and AI language
Deep experience building production-grade backend systems (FastAPI, Django, Flask)
Strong fundamentals in distributed systems, APIs, and system design
Hands-on experience integrating AI/ML systems (LLMs preferred) into backend services
Strong hands-on experience building or working with agentic systems, LLM orchestration, or RAG architectures
Solid frontend exposure (React/Next.js or equivalent) with product thinking
Strong understanding of databases (SQL/NoSQL), caching, and async processing
Track record of hiring and developing strong engineers
High ownership mindset with bias for action
Nice To Have
Experience in Insurtech, Fintech, or high-scale marketplaces
Experience with real-time systems, event-driven architecture, or streaming pipelines
Familiarity with the Python AI ecosystem (PyTorch, TensorFlow, LangChain, etc.)
What Success Looks Like (612 Months)
Built and scaled Python-based backend systems powering AI products in production
Launched multiple AI-driven features used by customers/agents at scale
Established strong backend and AI engineering foundations
Built a high-ownership, high-caliber team
Delivered measurable business impact through shipped systems