Lead AI Developer

Experience 

The ideal candidate should have 8+ years of experience in the Web Development and minimum 4 years of experience in AI and machine learning, with a strong background in designing, deploying, and managing AI-driven automations, applications for content and multimedia development. Candidate should demonstrate expertise in leading cross-functional teams (frontend, backend) to deliver AI-powered solutions for multimedia and interactive content. Proficiency in Azure and other AI tools, machine learning models, and familiarity with eLearning industry standards are highly desirable.

Job Purpose 

Your role’s objective is to deliver AI driven automations and applications. These applications and automations are to optimizing and elevating eLearning development processes and enhancing the learning experience. The focus is on driving innovation to streamline workflows, reduce manual effort and thus bugs/errors, and deliver high-quality, engaging learning experiences.

Responsibilities

·      Collaborate with AI Architects to understand solution design, business logic, and simulation requirements, and implement them into scalable AI-driven applications

·      Work closely with frontend, QA, and product teams to develop and refine AI-powered user flows, decision logic, and interactive learning experiences

·      Develop and integrate LLM-powered features (e.g., GPT models) for simulation scenarios, dynamic content generation, and learner interactions

·      Build and optimize agentic AI workflows (multi-step reasoning, tool usage, feedback loops) using frameworks such as LangChain or Semantic Kernel

·      Implement RAG-based pipelines to enable context-aware responses using structured and unstructured learning content

·      Develop AI-driven simulation logic including decision branching, scoring mechanisms, adaptive feedback, and performance tracking

·      Build services for personalized learning paths, learner analytics, and real-time feedback within simulation environments

·      Design, build, and maintain data pipelines and preprocessing workflows to prepare high-quality content for AI models and simulations

·      Integrate AI capabilities with enterprise systems such as LMS/LXP (SCORM, xAPI, LTI), CMS, and other platforms via APIs

·      Implement Responsible AI guardrails, including input/output validation, prompt safety, and data privacy controls aligned with standards such as GDPR and ISO 27001

·      Support MLOps/DevOps workflows, including CI/CD integration, model deployment, monitoring, and performance optimization

·      Leverage AI-enabled tools for content automation (audio narration, translation, image/video generation) to enhance eLearning development efficiency

·      Document AI components, workflows, and integration patterns; provide technical support and knowledge sharing to development and L&D teams

Key Skills

·      LLMs: GPT models, LLaMA; prompt engineering, RAG, and agentic AI workflows using LangChain or Semantic Kernel

·      Backend & APIs: Python (FastAPI/Flask), JavaScript (Node.js), RESTful API development and integration

·      Data & RAG: Vector databases (Pinecone, FAISS, Azure AI Search), data processing (Pandas, NumPy), ETL pipelines for structured/unstructured data

·      Simulation Logic: Decision engines, scoring systems, adaptive learning, and real-time feedback mechanisms

·      Cloud & Deployment: Microsoft Azure / Amazon Web Services / Google Cloud Platform; compute, storage, managed AI services, Docker

·      MLOps & DevOps: CI/CD (GitHub Actions, Azure DevOps, Jenkins), MLflow (or equivalent), monitoring and logging

·      Integration: LMS/LXP standards (SCORM, xAPI, LTI), REST APIs, webhooks, microservices

·      Security & Responsible AI: Prompt safety, input/output validation, data privacy (GDPR basics), secure API access

·      Content Automation: AI tools for audio, video, and image generation (e.g., Adobe ecosystem) for eLearning workflows                                                                                                                                

Qualification –

·      Bachelor’s/ Master’s degree in - Computer Science/Computer Engineering/Data Science.

·      Specialization in AI, machine learning.

·      Microsoft Certified: Azure AI Engineer Associate

·      Demonstrated ability to implement AI solutions in content and multimedia development.

·      Excellent communication and teamwork skills to collaborate with instructional designers and technical teams.