Senior Data Engineer - Forward Deployed - Industrial AI
First seen by Alion on Nov 3, 2026.
Senior Data Engineer (Forward Deployed), Industrial AI Co-workers
A stealth industrial AI startup | Full-time | India (on site at customer plants, 50 - 60% of the time) | 5 - 8 years' experience
Put AI co-workers on the plant floor, and prove they work.
About Us:
We are a stealth industrial AI startup in Germany and India, building AI co-workers that work alongside plant teams. Our founding team brings 40 years of combined industrial and VC-backed startup experience, including IIT and IIM alumni, and you will work with them directly.
We start with maintenance. Skilled maintenance people are in short supply: about 409,000 US manufacturing jobs were unfilled in August 2025, and up to 1.9 million could go unfilled by 2033, with industrial maintenance technicians among the fastest-growing roles (Deloitte, 2025; Deloitte and The Manufacturing Institute, 2024). That makes it harder to keep machines healthy, and unplanned downtime already costs the world's 500 largest companies an estimated $1.4 trillion a year (Siemens, 2024). AI co-workers can help close that gap.
Our first AI co-worker helps manufacturers cut maintenance costs and downtime. It is in a proof of concept (POC) with large manufacturers, and you would help take it to live plants.
The Role:
We are looking for someone who has worked with plant or SAP data, judges whether data is right, works well with plant people, and uses AI tools such as Claude Code for the heavy coding. As our first Senior Data Engineer, you will make plant data usable, from connecting to plant systems (mainly SAP) to getting our AI co-worker live and reliable on site, and shape how we do this at every plant. You will work directly with the founders and plant maintenance, stores and IT teams.
What You Will Do:
- Connect to plant systems (mainly SAP, also other maintenance systems) and bring in equipment, work order, maintenance and spare-parts data, deploying in the customer's cloud or on-premise environment.
- Clean and link that data: remove duplicate parts, fix descriptions and units, and link parts to equipment. Build and run the pipelines (Python, SQL, PySpark) behind this.
- Check that the data and the AI co-worker's answers are correct, and fix them when they are not.
- Monitor pipelines and agents in production (alerting, data-quality and drift checks) and debug data, integration and model issues.
- Work with plant maintenance, stores and IT teams on site.
- Feed what you learn at plants back into the product and help ship fixes quickly.
- Set data engineering standards for plant deployments (validation, schemas, CI/CD, security) and, as the team grows, mentor other engineers.
What You Bring:
Must have:
- 5 - 8 years in data engineering, including manufacturing plant data (for example SAP PM or MM, plant IT or industrial data projects)
- Strong Python and advanced SQL, with hands-on experience building data pipelines on large datasets and working with APIs. You use AI coding tools such as Claude Code well, and can work without them if plant IT restricts them.
- Experience cleaning messy business data (duplicates, inconsistent records), with the judgement to tell whether data is right, and with workflow orchestration (for example Airflow).
- Clear communicator who is comfortable with both a plant storekeeper and a plant head, and can work within customer IT/OT security and access restrictions.
- Based in India, willing to spend 50 - 60% of your time on site at plants across India, including multi-week stays.
Nice to have:
- Familiarity with maintenance and spare-parts concepts (criticality, min/max levels, lead times).
- Working knowledge of LLMs, RAG and vector databases, and familiarity with agentic frameworks.
- Extracting data from PDFs, scanned documents and manuals using OCR.
- Experience with a major cloud (AWS, Azure or GCP), Docker or Linux.
- Prior experience at an early-stage startup or in a customer-facing technical role.
Not every box ticked? Strong data engineering fundamentals matter most, so apply if industrial AI excites you.
Why Join Us:
- Work on a problem that matters: help build the AI workforce that fills manufacturing's skills gap.
- Real ownership: join at the founding stage, own deployments at customer plants from day one, and shape the product.
- Visible impact: see your work reduce maintenance costs, stock-outs and breakdowns on a real shop floor, not just in a dashboard.
- Learn from people who have done this before: founders with 40 years of combined industrial experience who have deployed industrial AI hands-on.
- Grow with the company: get in early, with scope to grow as the team scales.
- Competitive compensation, plus ESOPs (details shared during the interview process)
How to Apply:
If you want to put AI to work on the factory floor, send your CV and a short note on a data or deployment project you are proud of. As we are in stealth, we will share more about the company and product when we speak.
Skills
Data Engineering, Python, SQL, SAP PM, SAP MM, PySpark, Generative AI, RAG, Agentic AI, Apache Airflow, Optical Character Recognition