Track Lead

Experience: 4 to 7 years

Location: Others, India

Skills: Python, ML frameworks, PyTorch, TensorFlow, Scikit-learn, Agentic AI systems, multi-agent frameworks, autonomous workflows, orchestration patterns, LLM application frameworks, LangChain, Semantic Kernel, AutoGen, RAG, Retrieval-Augmented Generation, vector databases, FAISS, Pinecone, Azure AI Search, prompt engineering strategies, evaluation pipelines, guardrails, API development, microservices architecture, FastAPI, Flask, cloud platforms, Azure, Azure OpenAI, AI Studio, Functions, Kubernetes, CI/CD, MLOps, data engineering pipelines, Spark, Databricks, GitHub Copilot, Microsoft 365 Copilot

Job Summary
Experience: 4–7+ years in AI/ML engineering, with at least 2+ years in Generative AI / LLM-based systems Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn) Hands-on experience building Agentic AI systems (multi-agent frameworks, autonomous workflows, orchestration patterns) Experience with LLM application frameworks such as LangChain, Semantic Kernel, AutoGen, or equivalent Solid understanding of RAG (Retrieval-Augmented Generation), vector databases (FAISS, Pinecone, Azure AI Search) Experience designing prompt engineering strategies, evaluation pipelines, and guardrails Solid skills in API development and microservices architecture (FastAPI, Flask) Familiarity with cloud platforms (Azure preferred) including Azure OpenAI, AI Studio, Functions, Kubernetes Experience with CI/CD, MLOps, and deploying ML/AI solutions at scale Strong problem-solving skills and ability to design end-to-end intelligent systems

Experience
8+ years total, with deep exposure to enterprise AI use cases Experience building multi-agent autonomous systems with reasoning, planning, and tool use Knowledge of graph-based workflows and orchestration frameworks Experience in fine-tuning LLMs and working with open-source models (Llama, Mistral, etc.)



Familiarity with evaluation frameworks (prompt testing, hallucination detection, safety benchmarking) Experience with real-time streaming data systems and event-driven architectures Exposure to Responsible AI practices, governance, and model risk management Experience in data engineering pipelines (Spark, Databricks) is a plus Strong collaboration and stakeholder management skills in enterprise environments

AI Skills Expectation:
All contractor resources are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of their day-to-day responsibilities:

Consistent Use:
Maintain a minimum of 90% weekly usage of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other approved GenAI platforms.

Applied Productivity
Leverage AI tools to enhance

Code generation and debugging
Documentation and technical writing
Data analysis and insights generation
Decision-making workflows

Continuous Learning:
Stay current with evolving AI capabilities and apply new features, tools, and patterns to improve delivery quality, speed, and innovation.

Key Responsibilities
Design and develop Agentic AI systems that can autonomously perform complex workflows using LLMs and tools Build and optimize RAG pipelines, multi-agent orchestration, and decision-making frameworks Develop scalable APIs and services to integrate AI capabilities into enterprise applications Implement evaluation, monitoring, and guardrails to ensure reliability, safety, and performance of AI systems Collaborate with cross-functional teams to translate business problems into AI-driven solutions

Other Requirements
Experience in enterprise AI transformation initiatives Domain exposure to Healthcare is a plus Experience building automation platforms, copilots, or AI assistants Background in data science, applied ML, or distributed systems engineering Experience working in Agile product teams delivering AI-powered applications

📌 Track Lead (Mumbai)
🏢 HCL Technologies
📍 Mumbai