Green Rock Innovations is hiring: Head of AI Engineering & Products Green Rock Innovations is a climate tech and infrastructure technology company reengineering the raw material layer of Indian construction. We recycle decades-old, weathered rock into certified, low-carbon construction material, and we are building the marketplace and technology infrastructure that will define how that material moves at national scale. We are now looking for an exceptional leader to serve as our Head of AI Engineering division to direct and lead the team.

In this role, you will define the intelligent architecture of our entire physical and logistical footprint. You will hold ultimate accountability for our automation architecture, determining what our AI systems are trusted to decide independently, what requires human sign-off, and how we measure system reliability over time. CORE RESPONSIBILITIES

AI Product Strategy & Architecture: Own the multi-year roadmap for machine learning and AI applications across sourcing, dispatch, quality assurance, and demand forecasting. You will make critical build-versus-buy decisions, evaluate fine-tuning versus retrieval-based (RAG) architectures, and determine when classical ML models outperform large language models (LLMs).

Autonomy & Reliability Frameworks: Define strict confidence thresholds, risk parameters, and escalation logic for all automated systems. You will architect our evaluation engine, including offline evaluation sets, held-out test data, shadow deployments, and production drift detection. You hold the authority to grant, audit, or revoke operational autonomy based on performance data.

Data Foundation & Infrastructure:



Establish ironclad data contracts, schema designs, entity resolution protocols, and lineage tracing from raw data inputs to final model inference. You will identify and resolve pipeline bottlenecks across quarry, plant, and logistics operations to ensure clean, reliable, and traceable data ingestion.

Team Leadership & Scale: Scale and lead a high-performing team of engineers and scientists. You will transition early-stage operational pilots into hardened, production-grade tools that our field sites rely on daily.

QUALIFICATIONS & EXPECTATIONS

Experience: 8 to 10 years of deep tech startup experience, including a proven track record within fintech, algorithmic trading, or financial infrastructure companies. You must have personal experience owning the line between automated decisioning and human review, and defending that boundary to regulators or institutional auditors.

Technical Depth: A Bachelor's or advanced degree in Computer Science, Engineering, Financial Engineering, or a highly quantitative field. You must possess deep technical fluency in MLOps, vector search, embedding pipelines, feature stores, and model evaluation methodologies. Hands-on Proficiency: Fluency in relevant languages sufficient to audit codebases, trace complex data pipelines end-to-end,



and mathematically validate model behaviors.

Leadership: Direct experience managing and developing technical engineering teams, with a focus on executing rigorous, first-principles engineering. WHO THIS ROLE IS NOT FOR

Professionals who prioritize theoretical model complexity over the real-world operational decisions the model is built to make.

Leaders who expect underlying data engineering or pipeline issues to be solved entirely by separate infrastructure teams.

Anyone uncomfortable serving as the final gatekeeper to delay or halt a deployment if the system fails to transparent established statistical reliability bars. If you don't match this exact description or lack formal credentials but know you can operate at this level, have scaled complex projects, and simply have the right operational chill vibe for our high-accountability culture, feel free to drop an email to [email protected] directly. COMPENSATION

This is an executive-level, outcome-owning position.

Compensation is benchmarked directly against top-tier fintech and applied AI product leadership pay structures, not standard industrial or infrastructure scales. The package includes a competitive fixed base, performance incentives, and long-term equity.

To Apply: If you are qualified to lead this mandate, please reach out directly via message or email [email protected]. Please include a summary of the most complex automation threshold you have previously built, scaled, or defended. #AIProductManagement #AppliedAI #DataEngineering #Fintech #Infrastructure #MachineLearning #MLOps

📌 Head of AI Engineering & Products (Kozhikode)
🏢 Green Rock innovations
📍 Kozhikode