Lead AI Engineer

Job Title: Lead AI Engineer
Location: Bangalore
Work Mode: Onsite / WFO
Experience: 8–12 years
Education: Bachelor's/Master's in Computer Science Engineering or related field ( preferred but not mandatory)
Budget/CTC: Up to 40 LPA
Notice Period: 30 days preferred

Roles & Responsibilities

Lead end-to-end AI solution development — from architecture design through production deployment
Own AI system design with a strong emphasis on LLMs and Retrieval-Augmented Generation (RAG)
Drive creation of comprehensive POCs and data-driven AI strategies for client/business problems
Guide cross-functional teams (data engineers ML engineers product) and manage stakeholder expectations across Pharma Retail or CPG domains
Own technical decision-making on model selection RAG architecture cloud infrastructure and MLOps practices
Mentor and upskill junior/mid-level AI engineers
Present AI strategy and solution trade-offs to both technical and business stakeholders

Mandatory Skills

Python SQL
AI system design & end-to-end AI solution development (LLMs & RAG)
Cloud platforms — Azure / AWS / GCP
Data & AI solutioning (data pipelines feeding AI systems)
8–12 yrs total experience with demonstrable lead-level ownership of AI projects

Good to Have

Domain experience in Pharma Retail or CPG
End-to-end POC development experience
Leadership in AI project delivery (team lead/manager track record)
MLOps / CI-CD practices for AI pipelines

Must-Have Soft Skills

Leadership and people management
Strategic thinking and decision-making
Stakeholder management
Effective communication (technical ↔ non-technical)

Good-to-Have Soft Skills

Mentoring and coaching junior team members
Ability to convey complex domain concepts to mixed audiences

Required Skills:

Python SQL Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) AI Solution Architecture End-to-End AI Solution Development Generative AI (GenAI) AI System Design AI/ML Solutioning Cloud Platforms (Azure / AWS / GCP) Data Pipelines for AI Systems AI Model Deployment & Productionization Proof of Concept (POC) Development AI Project Leadership MLOps CI/CD for AI Pipelines Stakeholder Management Team Leadership & Mentoring Architecture Design & Technical Decision-Making