AI Lead

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,