GenAI GTM/Solutions Architect at exl Service.com (India) Private Limited

Key Responsibilities:

Solution Architecture & Technical Leadership

• Design and understand GenAI architecture across cloud platforms (Azure, AWS, GCP).
• Lead client workshops to understand business challenges and translate them into AI-driven solutions. Promote existing EXL AI Solutions, from fine-tuned LLMs, Agentic AI Agents, Knowledge Graphs, advanced RAG pipelines, LLMOps and AI infrastructure.
• Architect LLM-based systems using GPT-4, Claude, Gemini, Llama2, and Mistral, including RAG pipelines, PEFT fine-tuning, and Agentic AI Agents orchestration w/ LangGraph.
• Ensure responsible AI practices, governance, and compliance with data privacy standards.

Sales Enablement & GTM Strategy

• Selling AI Solutions
• Partner with sales teams to co-create proposals and solution narratives.
• Develop and deliver product demos tailored to client use cases, leveraging sandbox environments and low-code tools.
• Create GTM materials including pitch decks, demo scripts, and proof-of-concept presentations.
• Support pre-sales activities, including technical Q&A, objection handling, and competitive positioning.

Cross-Functional Collaboration

• Work closely with data scientists, engineers, and product managers to ensure seamless solution delivery.
• Contribute to thought leadership through whitepapers, webinars, and internal enablement sessions.
• Capture and share best practices across the AI architect community.

Technical Responsibilities:

• AI Architecture Innovation Research & Design: Our mantra is Innovation at Speed. Focus on new innovative methods of designing and architecting AI and GenAI systems and be able to grasp and adapt monthly and weekly AI innovation coming out in the industry and apply it to our clients’ use cases and needs in new modern ways.
• Client Advisory & Solutioning: Engage directly with senior client stakeholders (including C-suite) to understand complex business challenges, identify opportunities for GenAI and Agentic AI, and define project scope.
• Workshop Facilitation: Design, lead, and facilitate high-impact client workshops and strategy sessions focused on identifying and prioritizing Generative and Agentic AI use cases and roadmap development.
• Technical Leadership & Architecture: Design, architect, and oversee the development and deployment of scalable, robust, and cutting-edge Generative AI and sophisticated Agentic AI systems (including multi-agent workflows) for client and internal projects.
• Project & Engagement Leadership: Lead large-scale, complex Generative AI and Agentic AI projects from strategic conception through successful deployment, managing cross-functional teams (internal and client-side) and ensuring timely delivery of high-quality solutions.
• Technical Mentorship: Mentor and guide technical teams (data scientists, data and AI engineers) in best practices for advanced AI development, deployment, MLOps/LLMOps, and agentic system design.
• Stakeholder Management: Build and maintain strong relationships with key internal and external stakeholders, effectively communicating complex technical concepts and project progress.
• Quality & Best Practices: Ensure adherence to rigorous software engineering principles, Agile methodologies, and responsible AI practices throughout the solution lifecycle.
• Stay Current: Maintain deep expertise in the latest trends, research, tools, and technologies within Generative AI, Large Language Models (LLMs), and Agentic AI paradigms.

Qualifications:

• Bachelor's degree in computer science, AI, Machine Learning, or a related quantitative field. Master's or Ph.D. strongly preferred.
• 5+ years in AI/ML solution architecture, technical sales, or pre-sales engineering. Proven experience with GenAI technologies, LLMs, and orchestration frameworks (LangChain, LangGraph, AutoGen).
• Demonstrated track record of successfully architecting and deploying large-scale AI projects, preferably including complex GenAI and/or Agentic AI applications in enterprise or client settings.
• Prior experience in technology consulting or a client-facing technical specialist role within a technology provider is highly advantageous.
• Excellent presentation skills with proficiency in PowerPoint and storytelling for executive audiences.
• Hands-on experience with demo environments, sandbox setup, and client-facing proof-of-concepts.
• Excellent communication and stakeholder management skills.
• Experience working effectively with global teams across multiple geographic locations is a plus.

Preferred Skills/Qualifications:

• Proven ability to lead and motivate diverse, global teams
• Excellent communication skills, capable of explaining complex AI concepts to various stakeholders
• Project and program management skills and experience working in Agile environments
• Experience with agentic AI workflows and autonomous agents.
• Background in industries such as insurance, healthcare, banking, or retail.
• Prior exposure to GTM strategy, sales enablement, and marketing alignment.
• Programming & Libraries: proficiency in Python and experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). Experience using Cursor, Windsurf, Replit, and Github Copilot.
• LLM Expertise: Experience developing applications leveraging state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering, fine-tuning, and evaluation.
• GenAI & Agentic Frameworks: Hands-on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex, Langfuse) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph, agent planning, tool use integration, multi-agent collaboration).
• AI Architecture: Deep understanding of AI/ML system architecture patterns, including microservices, event-driven architectures, and patterns specific to RAG (Retrieval-Augmented Generation), Graph RAG, Agentic RAG, and multi-agent systems.
• Data: Knowledge of industry approaches to data engines and data labeling like Scale.ai and Mercor. Experience with auto data-labeling and synthetic data generation techniques.
• Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS).
• Advanced AI Concepts: Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for complex AI systems.
• Software Engineering: Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems.
• Cloud Platforms: Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, GCP), including their AI/ML services.
• LLMOps/MLOps: Expertise in designing and implementing robust MLOps/LLMOps pipelines for automated testing, CI/CD, monitoring, and governance of complex AI models and applications.

The typical base pay range for this role across the U.S. is USD $165,000 - $220,000 per year.

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits