• Context
  
  

Why This Role Exists

EduBridge Group runs three business lines

EduBridge, BridgeBeyond, and TalentDeploy scaling toward 150 Cr revenue by FY

• The Product & Learning Solutions team is the group capability supplier : we build the platforms, integrations, and intelligent systems that make learning and delivery possible at scale.
  
  

Several of our internal products currently built and run by an intern team have crossed proof-of-concept. They are useful, but they are fragile, undocumented, and dependent on individuals who will move on. They now need a senior owner who can harden them for production and evolve them into AI-powered platforms that scale.

This role is created for that owner.

• The Mandate
  
  

You will take complete end-to-end ownership of the intern-built product portfolio from Day 1

code, architecture, infrastructure, deployment, roadmap, and stakeholders. Within 90 days, these products must transition from

"fragile prototypes"

to

"production-grade, observable, documented, scalable systems."

Beyond stabilization, you will drive the

AI/ML layer across our products embedding intelligent automation, personalization, content generation, and predictive analytics where they create measurable business value.

• What You'll Own
• Product Ownership (End-to-End)
  
  

Take complete handover of all intern-developed products: code, infra, integrations, documentation

Establish source control, CI/CD, testing standards, and deployment discipline

Build proper architecture documentation, runbooks, and observability

Own the 12-month product roadmap in partnership with business stakeholders

• Full-Stack Engineering
  
  

Backend

Python (Django / FastAPI), REST APIs, microservices, async processing

Frontend

React (or equivalent modern framework), responsive UI

Data

PostgreSQL / MySQL / MongoDB; data modeling and migrations

Cloud & DevOps

AWS (we run on AWS

EC2, S3, RDS, Lambda); CI/CD pipelines

Integrations

Internal platforms (ELITE LMS, Do-Select, partner APIs, NSDC-SIDH, Tata Tele) and third-party APIs

• AI/ML Engineering
  
  

Design, train, and deploy ML models for: learner personalization, content recommendation, automated assessment, retention prediction, document/OCR automation

Ship LLM-powered features in production (RAG, agentic workflows, content/assessment generation) using leading commercial and open-source models

Build evaluation pipelines, guardrails, and cost-monitoring for AI features this is non-negotiable

Translate emerging AI capability into concrete business application

• Cross-Functional Leadership
  
  

Single point of accountability for these products in business reviews

Translate problems from L&D, Service Excellence, PPV, and HR into product features

Mentor interns and junior developers as the team grows under you

• Must-Have
  
  

58 years of full-stack engineering experience, with at least 2 years deploying AI/ML in production

(not just notebooks)

Strong Python (Django or FastAPI) + frontend competence (React preferred)

Hands-on AWS experience and production database expertise

Demonstrated experience with

LLMs in production

RAG, prompt engineering, model orchestration, evaluation

Track record of taking over and stabilizing legacy or poorly-documented codebases

(this is critical for the first 90 days)

Strong written communication architecture docs, decision logs, technical specs

• Good-to-Have
  
  

EdTech, HRTech, or workforce-development domain experience

Familiarity with LMS, SCORM/xAPI, assessment engines

MLOps tooling (MLflow, SageMaker, Vertex AI)

Vector databases (pgvector, Pinecone, Weaviate)

Indian language NLP / regional speech processing experience