Senior Engineering Lead - Edge AI Systems

Location: Kochi (on-site preferred)

Reports to: Head of Engineering / CTO

About the Role

We're looking for a hands-on Senior Engineering Lead to own delivery of Flagman, our edge AI computer vision platform deployed in industrial environments. You'll lead a team of 6 engineers spanning embedded systems, ML/computer vision, and cloud infrastructure — while staying in the code yourself. This is a player-coach role: you're accountable for timelines and release quality, and technically credible enough to unblock the team when it matters.

What you will do

Own project planning, sprint execution, and release timelines across embedded, ML, and infrastructure workstreams; flag risks and slips early with credible mitigation plans
Break ambiguous product requirements into scoped, estimable work and manage cross-track dependencies
Review and contribute code across the stack: Python ML pipelines (detection, tracking, edge inference), embedded Linux in C++ (GStreamer, GPIO, systemd), and backend services (Go, PostgreSQL)
Lead design reviews for high-stakes changes and personally take on critical-path tasks when the team is stretched
Debug production issues on real hardware in the field
Manage, mentor, and grow the team: 1:1s, goals, feedback, performance conversations, and hiring
Coordinate with field engineering on deployments and customer escalations

What we are looking for:

Must-have

8+ years of engineering experience, with 2+ years leading a team
Track record of shipping hardware-adjacent or embedded products on committed timelines
Strong hands-on skills in at least two of: embedded Linux with C++ exposure, ML inference/deployment (PyTorch, ONNX), backend services (Go or Python, PostgreSQL) — and able to review code across all three
Confident with AI-assisted coding workflows, using them to accelerate delivery without compromising quality
Clear written communication: status updates, design docs, postmortems

Strong plus

Edge AI / computer vision product experience (camera systems, video pipelines)
Industrial automation exposure: PLCs, industrial protocols, sensors
CI/CD for embedded targets and on-device testing