Job Title: AI Lead Experience: 8–10 Years Location: Remote Notice Period: Immediate Joiners Only

About the Role

We are seeking an experienced AI Lead to design, build, and scale next-generation Agentic AI systems capable of autonomous reasoning, planning, and task execution. This role requires a strong blend of expertise in Generative AI, Machine Learning, MLOps, and cloud-native architectures. As an AI Lead, you will drive the technical vision for intelligent AI solutions, architect multi-agent systems, lead engineering teams, and ensure successful deployment of production-grade AI applications. You will work closely with cross-functional stakeholders to deliver scalable, reliable, and innovative AI-powered products.

Key Responsibilities

Agentic AI & LLM Engineering Design, develop, and orchestrate multi-agent AI systems capable of autonomous reasoning and decision-making. Architect and implement LLM-powered workflows using frameworks such as LangChain, LangGraph, CrewAI, and AutoGen. Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise-scale AI applications. Design agent memory architectures, context management strategies, and long-term knowledge retention mechanisms. Integrate external tools, APIs, databases, and third-party services into AI agent workflows. Optimize prompt engineering strategies and implement advanced prompting techniques for production use cases. Machine Learning & AI Development Build, train, deploy, and maintain machine learning models for classification, ranking, recommendation, anomaly detection, and predictive analytics. Fine-tune foundation models and LLMs using techniques such as LoRA, PEFT, quantization, and instruction tuning. Develop scalable NLP solutions leveraging transformers, embeddings, and vector search technologies. Define model evaluation frameworks using metrics such as F1 Score, Precision, Recall, AUC, and other business-specific KPIs. Implement feature engineering, model validation, and experimentation workflows. MLOps & Infrastructure Establish end-to-end MLOps pipelines for model training, deployment, monitoring, versioning, and governance. Implement CI/CD workflows for AI and ML systems. Deploy AI solutions on cloud platforms including AWS, GCP, and Azure. Build scalable infrastructure using Docker, Kubernetes, Terraform, and cloud-native services. Ensure observability, monitoring, and performance optimization of AI systems. Leadership & Architecture Lead architecture decisions for AI and ML initiatives across the organization. Mentor AI/ML engineers and provide technical guidance on best practices and emerging technologies. Collaborate with product, engineering, and business teams to align AI capabilities with strategic objectives. Drive innovation through evaluation and adoption of emerging AI technologies and research advancements. Required Qualifications 8–10 years of overall experience in Software Engineering. Minimum 4+ years of hands-on experience in AI/ML engineering and production AI systems. Proven expertise in building and deploying Agentic AI and Autonomous AI solutions. Strong experience with Large Language Models (LLMs), prompt engineering, fine-tuning, and model optimization. Proficiency in Python and modern AI frameworks including LangChain, LangGraph,