Description
AI & Generative AI
Large Language Models (OpenAI, Claude, Gemini, Llama, Mistral)
Generative AI and Agentic AI architectures
Retrieval-Augmented Generation (RAG)
Prompt Engineering
Multi-Agent Systems
AI Orchestration Frameworks (LangChain, LangGraph, CrewAI, AutoGen)
Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)

Machine Learning & Data Science
Machine Learning and Deep Learning fundamentals
Model evaluation, deployment, and monitoring
Feature engineering and data pipelines

Programming & Cloud
Python (mandatory)
AWS, Azure, or GCP
REST APIs and Microservices
MLOps / LLMOps
Docker and Kubernetes

Architecture & Consulting
Enterprise Solution Architecture
Technical Consulting and Pre-Sales
Requirements Gathering and Solution Design
Stakeholder Management
Executive Presentations and Customer Workshops

Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
10–15+ years of experience in software engineering, AI/ML, data science, or solution architecture.
Proven experience delivering enterprise AI/GenAI solutions in production settings.
Solid customer-facing and leadership experience.

Preferred Qualifications
Certifications in AWS, Azure, GCP,



or Generative AI.
Experience with Responsible AI, AI Governance, and Security.
Exposure to Telecom, BFSI, Retail, Healthcare, Manufacturing, or Supply Chain domains.

Responsibilities
Lead end-to-end AI solutioning activities, including discovery, architecture, design, development, and deployment.
Engage with business stakeholders, customers, and leadership teams to identify AI opportunities and define solution roadmaps.
Design and implement Generative AI, Agentic AI, and Machine Learning solutions aligned with business objectives.
Architect enterprise-grade AI applications leveraging LLMs, RAG frameworks, AI agents, vector databases, and cloud platforms.
Collaborate with pre-sales and delivery teams for solution proposals, effort estimation, and technical presentations.
Define scalable AI architecture, governance frameworks, security controls, and best practices.
Guide engineering teams through implementation, code reviews, and deployment strategies.
Drive innovation by evaluating emerging AI technologies, frameworks, and industry trends.
Mentor AI engineers, data scientists, and architects while fostering technical excellence.

📌 Senior Process Manager Pune (India)
🏢 eClerx
📍 India