Wattr.ai
Website:
wattrunner.com
Company:
https://www.linkedin.com/company/wattr-ai
Seniority: Director
Industries: Utilities Administration
Job details:
Job Description:
Location: Chandigarh Tricity | Full-time | Work from Office
Experience: 7+ years
Compensation: Competition pay + meaningful ESOPs
If you have recently scaled production systems and are excited by the opportunity to own architecture across the full technology stack at a growing deep-tech company, this might interest you.
And, Chandigarh Tricity offers better AQI, lower living costs, calmer lifestyle, deeper focus :)
About Wattr.ai
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Wattr.ai is a mission-driven deep-tech cleantech company building technology for real-world challenges across water, agriculture and power infrastructure.
Our technology is being deployed across India, connecting IoT devices, sensors, cloud systems, data platforms, AI/ML and applications.
We are a scaling startup, and technology will be a critical competitive advantage as we grow. We are looking for a Technical Architect who can build the architecture and engineering foundation for this next stage.
About the Role
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As Technical Architect, you will own the end-to-end technical blueprint of our platform — from edge devices and sensor ingestion, through cloud infrastructure and data pipelines, to AI/ML services and the web/mobile applications customers interact with.
You will set the architectural direction, make major technology bets, write production code when it matters, review designs, mentor senior engineers and work closely with the founders on product and platform strategy.
This is a hands-on architect role, not a purely managerial or documentation-focused position.
Recent experience scaling production systems is highly preferred. We are particularly interested in someone who has recently taken systems through significant growth in scale, complexity, users, devices or data volume and understands the architectural challenges that come with scaling.
What You’ll Own:
End-to-end & enterprise architecture
- Own architecture across IoT/sensors/controllers → ingestion → cloud/backend → data pipelines → AI/ML → web/mobile applications.
- Define and evolve service boundaries, data contracts, event flows, storage choices and deployment topology across cloud and on-prem environments.
- Design APIs and integration contracts across device, web and mobile surfaces.
- Maintain a clear enterprise-level view of how systems, services and technology components fit together.
Scalability, reliability & distributed systems
- Design distributed and event-driven systems with practical consideration of consistency, availability, latency, fault tolerance and back-pressure.
- Own non-functional requirements including scalability, reliability, latency, security and cost, with clear SLOs and a roadmap to achieve them.
- Design systems that can scale significantly as deployments, devices, data and customers grow.
Cloud, infrastructure & production engineering
- Define and evolve architecture across AWS, GCP or Azure.
- Drive modern infrastructure practices including Infrastructure as Code, Kubernetes/container orchestration, Docker, CI/CD, observability and SRE practices.
- Establish standards for production readiness, monitoring, testing, security and release management.
Data, streaming & analytical systems
- Architect data-intensive systems involving high-volume ingestion, time-series data, stream processing, data lakes/warehouses and analytical workloads.
- Work with technologies such as Kafka, Kinesis and MQTT-based pipelines and select appropriate data platforms based on scale and requirements.
- Make sound technology choices across languages, frameworks, databases, message brokers, ML stacks and IoT protocols, based on technical requirements and long-term trade-offs.
IoT, edge & field realities
- Design for real-world constraints including intermittent connectivity, low-power devices and noisy sensor data.
- Evaluate and architect appropriate IoT protocols and platforms such as MQTT, LwM2M, OPC UA, LoRaWAN, NB-IoT, AWS IoT and Azure IoT Hub.
- Ensure reliable end-to-end operation across edge, device, network and cloud systems.
AI/ML architecture
- Architect the integration of AI/ML platforms and services into the broader product and data architecture.
- Evaluate opportunities involving edge AI, on-device ML, model deployment pipelines and MLOps at scale.
Technical leadership & engineering standards
- Establish and raise standards for architecture, code quality, testing, observability, security and release management.
- Lead design reviews, write clear RFCs/technical designs, and document the trade-offs behind major architectural decisions.
- Mentor senior engineers and raise the technical bar across the team.
- Translate ambiguous product goals into clear, practical and buildable technical plans.
Cross-functional & external technical engagement
- Partner with product, hardware and data science teams to ship features end-to-end and de-risk complex cross-stack initiatives.
- Participate in technical discovery, integration and deployment discussions with customers, integrators and government/utility partners.
- Evaluate build-vs-buy decisions and manage key technology partnerships and vendors.
What We’re Looking For
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Must-have
- 5+ years designing and shipping production software systems, with experience as a Technical Architect, Principal Engineer, Staff Engineer or equivalent.
- Strong practical understanding of distributed systems, event-driven architecture and enterprise architecture.
- Demonstrated experience scaling production systems, preferably in a recent role.
- Deep hands-on experience with at least one major cloud platform: AWS, GCP or Azure.
- Strong infrastructure experience including IaC, Kubernetes or equivalent, Docker, CI/CD, observability and SRE.
- Hands-on proficiency in at least two of: Python, Go, Java/Kotlin, TypeScript/Node.js, C/C++ or Rust.
- Experience designing data-intensive systems, including time-series ingestion, streaming, data pipelines, data lakes/warehouses and analytical workloads.
- Strong API design and system integration experience.
- Ability to make architecture decisions considering scale, reliability, latency, security and cost, with clear technical trade-offs.
- Strong written and verbal communication — able to write a clean RFC, explain architecture clearly and run effective design reviews.
- Comfortable remaining hands-on technically while providing architectural direction to the team.
Strong Plus - Experience in one or more of:
- IoT, industrial automation, edge computing or connected devices
- MQTT, LwM2M, OPC UA, LoRaWAN, NB-IoT, AWS IoT or Azure IoT Hub
- SCADA, telemetry or control systems
- Edge AI, on-device ML, model deployment or MLOps
- Water, agriculture, energy, power, infrastructure or cleantech
- Early-stage or scaling startups
- Taking products/systems from 0→1 and subsequently scaling them
- Real-world field deployments and unreliable connectivity environments
How You Work
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We are looking for someone who:
- Defaults to clarity in writing, architecture, diagrams and conversations.
- Can make decisions with incomplete information and revisit them when the data changes.
- Thinks beyond whether something works today to whether it will still make sense at 10x or 100x scale.
- Balances engineering quality with speed and business reality.
- Can move comfortably between detailed technical implementation and broader product/business strategy.
- Is comfortable going from a Kubernetes manifest to a board-level discussion when required.
- Cares about the long-term craft of the system, not just getting it shipped.
- Raises the technical bar for everyone around them.
What Success Looks Like
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- A clear, scalable technical architecture is established across edge, cloud, data, AI/ML and applications.
- The platform can reliably scale as devices, deployments, data and customers grow.
- Architectural bottlenecks and reliability risks are identified before they become production problems.
- Engineering teams follow strong standards for architecture, testing, security, observability and releases.
- Major technology decisions are deliberate, documented and aligned with product and business requirements.
- Complex cross-stack initiatives move from ambiguity to production efficiently.
- The architecture evolves into a competitive advantage as Wattr.ai scales.
Why Join Wattr.ai?
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- Own the technical blueprint of a real-world deep-tech platform.
- Join at a critical scaling stage, where architecture decisions will directly shape the company's next phase.
- Work closely with the founders and senior engineering team on product and platform strategy.
- Solve technically complex problems across IoT, distributed systems, data, AI/ML and cloud.
- Work with technology deployed across water, agriculture and infrastructure projects in India.
- Senior, high-ownership role with meaningful ESOP upside.
- Small, high-trust team with a short distance between a technical decision and its real-world implementation.
Click on Apply to know more.