AI Implementation and Enablement Lead-Kolkata

Stride India; Kolkata District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Stride India seeks an AI Implementation and Enablement Lead in Kolkata. Degree in CS with Generative AI, Large Language Models (LLMs), prompt engineering, and Retrieval-Augmented Generation (RAG). Working proficiency in Python and SQL, alongside API integration (FastAPI/Flask) and vector databases.

Exposure to major cloud platforms like AWS, Azure, or GCP and Docker. 3 to 8 years of practical experience in digital transformation, technical product deployment, or change management.

Qualifications

• Degree in Computer Science with Generative AI, LLMs, prompt engineering and RAG.
• Hands-on Python and SQL, API integration and vector databases.
• Exposure to cloud platforms (AWS/Azure/GCP/SAP BTP) and Docker.

Responsibilities

• Identify and build a prioritised AI use-case pipeline from cross-functional inputs.
• Deliver end-to-end AI solutions across Foundry operations, quality, Sales, and Finance.
• Enable the organisation with role-specific AI training and internal assistants.
• Own data plumbing, governance and monitoring of deployed models.

Skills

Technical AI Proficiency

Change Management & Enablement

GRC

Product & Project Management

SAP data extraction

Python/SQL/pandas/scikit-learn

LLM/RAG experience

Cloud deployment (AWS/Azure/GCP/SAP BT

Docker & MLOps monitoring

Train non-technical users on AI

Education

Degree in Computer Science

Tools

Docker

FastAPI/Flask

SAP HANA/Datasphere/BW

CDS views / OData / BAPI/RFC

Job description

AI Implementation and Enablement Lead-Kolkata -

Degree in Computer Science with Generative AI, Large Language Models (LLMs), prompt engineering, and Retrieval - Augmented Generation (RAG). Working proficiency in Python and SQL, alongside API integration (FastAPI/Flask) and vector databases. Exposure to major cloud5 platforms like AWS, Microsoft Azure, or Google Cloud and containerization tools like Docker.

Experience

3 to 8 years of practical experience in digital transformation, technical product deployment, or change management. At least two AI/ML or automation solutions taken to live production use.

Skills Required

• Technical AI Proficiency
• Change Management & Enablement
• Governance, Risk, & Compliance (GRC)
• Product & Project Management
• Hands-on SAP data extraction and integration — CDS views, OData services, BAPI/RFC, or SAP HANA / Datasphere / BW; comfortable navigating PP, QM, MM, PM and FICO data structures
• Strong Python, SQL, pandas, scikit-learn; experience with at least one deep learning framework
• Practical LLM and RAG experience — prompt design, evaluation, cost control, and clear-eyed about failure modes
• Cloud5 deployment (AWS/Azure/GCP or SAP BTP), APIs, Docker, basic MLOps and monitoring
• Demonstrated ability to train and carry non-technical users — you will spend real time on the shop floor and in the accounts department
• Ability to turn a vague operational complaint into a defined, measurable problem

Job Resposibility

1. Identify and build

• Run structured discovery with foundry operations, quality, sales and finance to build a prioritised use‑case pipeline, sized by effort and expected return
• Build proof‑of‑concepts fast, discard what doesn’t work, and take the rest to live production use

2. Deliver solutions across the business

Foundry operations & quality

• Rejection and defect analysis — correlating porosity, shrinkage, cold shut, inclusions and blowholes against furnace, moulding, sand and pouring parameters
• Charge mix optimisation against live scrap and ferroalloy prices, within chemistry limits
• Melt and energy analytics — power consumption per tonne, tap‑to‑tap time, furnace efficiency
• Sand plant analytics using sand lab test data (GCS, compactability, moisture, LOI)
• Spectrometer and heat‑record analysis for chemistry drift
• Vision‑based surface inspection at fettling, or AI‑assisted review of radiography/MPI results
• Predictive maintenance on induction furnaces, moulding lines, compressors and cranes
• Yield and OEE analysis by pattern, grade and line

Sales

• Demand forecasting by customer and casting; enquiry‑to‑order conversion analysis
• Casting cost estimation and quotation support — a major time sink in job‑order foundries
• Customer schedule variance and delivery‑risk prediction

Finance & Accounting

• Vendor invoice and PO data extraction, three‑way match automation
• Ledger and bank reconciliation, duplicate and anomaly detection
• Receivables prioritisation and collections risk scoring
• Automated MIS and management reporting from SAP data

3. Enable the organisation

• Run practical, role‑specific AI training for staff across functions — what these tools do well, where they fail, and how to use them without creating risk
• Build internal assistants and prompt libraries for repetitive work: drafting, summarising, report writing, data lookup
• Publish and enforce a simple internal AI usage policy covering confidential drawings, costings, customer data and financial records
• Track adoption and act as internal point of contact for AI questions

4. Own the plumbing and the governance

• Extract and model data from SAP alongside plant‑floor, lab and spreadsheet sources
• Evaluate tools and vendors; make honest build vs. buy calls
• Monitor deployed models, and ensure human review on anything touching financial, quality‑certification or compliance output.

CTC

As per industry standard

• Monday - Saturday : 10 a.m. – 6 p.m.
• Sunday: Closed