Senior Process Manager

Job description

**Job 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 environments. - Strong 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.