Job Title: Lead Video Analytics Data Architect

Experience: 5 - 8 years

Employment Type: Full-Time

Location: Kondapur, Hyderabad (Hybrid min 3 days a week in-office)

Team: Owns and leads the full technical build team (Data Scientist + 3 Interns)

ROLE SUMMARY :

Own the end-to-end technical architecture of the platform - from IP67 edge camera capture through computer vision inference to the SaaS dashboards used by kitchen operators, aggregators, and FSSAI regulators.

This is a hands-on leadership role for someone who has already taken at least 2-3 video analytics products from zero to production, ideally in kitchen, utility, or industrial/environmental-safety domains where wastage, hygiene, and safety KPIs were the core deliverable.

KEY RESPONSIBILITIES :

- Architecture ownership - design the full edge-to-cloud pipeline: IP67 camera capture, RTSP ingestion, edge inference nodes, MQTT-based event orchestration, and the cloud aggregation and dashboard layer.

- SaaS platform - direct development of the web application across both frontend and backend, covering the operator dashboard, aggregator API layer, and FSSAI regulator view.

- MLOps & model lifecycle - own model versioning, CI/CD for model deployment, automated retraining pipelines, and continuous production monitoring for drift, accuracy decay, and latency.

- KPI pipelines - define and enforce data-pipeline standards for hygiene, wastage, and environmental-safety KPIs (PPE compliance, cross-contamination, spill/pest detection, portion variance, storage segregation).

- Performance & reliability - set and hold the team to technical SLAs such as sub-2-second inference latency and 99.9% system uptime.

- Cloud & DevOps - evaluate and implement AWS or GCP infrastructure for secure, multi-tenant deployment across hundreds of outlets; build containerization, CI/CD, and observability practices.

- Team leadership - lead and mentor the Data Scientist and the three interns; run technical reviews and unblock delivery.

- Compliance by design - ensure the architecture meets DPDP Act 2023 and FSSAI requirements, including edge-anonymization of facial data for the Smilometer/Trust Score modules.

- Founder support - partner with the founders on technical due diligence for fundraising conversations and enterprise or regulator pilots.

REQUIRED SKILLS & QUALIFICATIONS :

- 5-8 years of software/ML engineering experience, including at least 2-3 video analytics projects taken from concept to live production.

- Prior experience in kitchen, utility, industrial, or environmental-safety monitoring domains strongly preferred - especially wastage tracking, hygiene compliance, or safety KPIs.

- Strong full-stack development ability - modern frontend framework (React or equivalent) and backend (Node.js/Python).

- Hands-on MLOps experience: model packaging, deployment pipelines, and monitoring/alerting for model drift.

- Solid grounding in computer vision fundamentals (object detection, action recognition), even without daily hands-on model training.

- Experience designing multi-tenant SaaS architectures - auth, role-based access, API design, dashboarding.

- Comfortable working with edge-compute devices and video streaming protocols (RTSP, MQTT).

PREFERRED / NICE-TO-HAVE :

- Working knowledge of AWS or GCP - compute, storage, IoT services, and managed ML platforms.

- Experience with Docker/Kubernetes and CI/CD pipelines.

- Exposure to regulated, compliance-heavy domains such as food safety, healthcare, or utilities.

- Prior 0-to-1 or early-stage startup product-building experience.