About the Role

Our client is building a mission-critical technology platform to improve water and wastewater operations at scale. We are looking for a Head of Engineering to lead end-to-end engineering across IoT, edge, cloud, data, ML systems, and applications, and to build a high-performing engineering organization that delivers reliable systems in real-world field conditions.

This role requires hands-on architectural ownership, strong execution capability, and proven leadership in fast-growing environments.

Key Responsibilities

Technology & Architecture Ownership

- Own end-to-end architecture across device-to-cloud, edge computing, backend services, data platforms, ML systems, and applications

- Design resilient, edge-aware systems that operate under unreliable connectivity, imperfect data, and real-world field constraints

- Make clear architectural trade-offs balancing reliability, scalability, speed, and maintainability

- Establish and enforce engineering standards for reliability, security, testability, and performance

Execution & Delivery

- Drive technical execution from concept to production across IoT, cloud, data, and ML systems

- Build robust device-to-cloud pipelines for industrial deployments

- Develop data and ML pipelines for monitoring, diagnostics, optimization, and - automated decision-making

- Implement automated testing and observability across devices, data flows, and applications

Leadership & Team Building

- Build, mentor, and scale a high-performing engineering team

- Set a culture of ownership, accountability, and operational excellence

- Enable teams to move fast without compromising system reliability

- Use AI tools pragmatically to improve engineering velocity, testing, and documentation

Cross-Functional Collaboration

- Work closely with Product and Operations to translate water-domain and operational knowledge into software systems

- Communicate clearly with technical and non-technical stakeholders

- Close the gap between knowledge - action - resolution in field operations

Required Qualifications

- B.Tech./M.Tech. in Computer Science with 10+ years of experience building and scaling complex systems (IoT, distributed systems, industrial software, or large-scale data platforms)

- Strong hands-on experience with cloud architecture (AWS / Azure / GCP)

- Working knowledge of IoT, edge computing, and automated equipment/control systems

- Proven experience deploying ML systems in production that deliver operational or business outcomes

- Prior experience leading engineering teams in startups or fast-growing companies

- Strong system design skills with real-world reliability and failure-mode thinking

- Ability to communicate clearly with technical and non-technical stakeholders

Preferred Skills

- Experience with device-to-cloud architectures

- Exposure to industrial or infrastructure environments (utilities, manufacturing, energy, water, etc.)

- Experience building systems that operate under imperfect data and connectivity

- Practical use of AI tools to improve development speed, testing, or documentation