Head - Engineering - Manufacturing/IIoT - IIT

Head - Engineering - IIT

The Role:

We are looking for a visionary and hands-on Head of Engineering to lead our diverse technical teams. You will bridge the gap between complex software engineering, big data infrastructure, and machine learning innovation.

You will own the technology roadmap, architecture, and delivery of our TiA platform, ensuring it is scalable, secure, and robust enough to handle high-frequency industrial data on AWS and Azure.

Strategic Leadership:

- Lead, mentor, and scale a high-performing engineering team.

- Foster a culture of technical excellence, agility, and innovation.

Architecture & Stack Ownership:

- Oversee the end-to-end architecture of the TiA platform, ensuring seamless integration between backend (Python/Node.js), frontend (React), and data pipelines (Databricks).

ML Integration:

- Collaborate closely with Data Science teams to operationalize Machine Learning models.

- You don't need to build models, but you must understand the ML lifecycle to build the infrastructure that supports them.

Cloud & Data Strategy:

- Manage multi-cloud environments (AWS & Azure) and oversee complex data pipelining strategies using Databricks to handle streaming industrial data.

Delivery Management:

- Drive the software development lifecycle (SDLC), ensuring timely releases and high code quality.

Must-Haves:

- Experience: 10+ years in software engineering with 4+ years in leadership roles (Engineering Manager, Head of, or VP level).

- Full-Stack Expertise: Deep architectural understanding of Python and Node.js backends, coupled with modern React frontends.

- Big Data & Cloud: Proven experience with Databricks for data pipelining and proficiency in cloud-native architectures on AWS and Azure.

- ML Fundamentals: Strong understanding of how software engineering supports AI/ML (model deployment, MLOps, inference pipelines).

- Database Knowledge: Experience with varied database technologies (Time-series, SQL, NoSQL) suitable for high-volume sensor data.

Nice-to-Haves:

- Experience in the Manufacturing, IIoT, or Industry 4.0 sectors.

- Familiarity with industrial protocols (OPC UA, MQTT).