• Design, build, and operate RAG solutions across semantic search to retrieval over structured data and knowledge graphs • Build agentic systems that perform multi-step tasks against enterprise data • Drive automation of internal processes and ship AI features into customer-facing products • Own retrieval quality end to end: chunking strategies, hybrid approaches, and evaluation • Evaluate and recommend tooling for AI stack and drive decisions together with architect • Author production services in Go (gRPC) and integrate them with AI router and existing platform

• Lead technical discovery sessions with enterprise customers to understand business objectives, deployment requirements, and success criteria. • Scope and execute proof-of-concepts, pilot programs, and production deployment initiatives. • Conduct load testing and evaluations to validate model architectures and deployment configurations. • Design and implement end-to-end AI solutions within complex enterprise environments. • Build production-grade AI and machine learning systems that meet enterprise performance, security, and compliance requirements. • Conduct model evaluations, benchmarking, and performance testing. • Advise customers on model selection strategies and deployment architectures. • Support fine-tuning methodologies, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Fine-Tuning (RFT). • Develop evaluation frameworks to measure model quality and business impact. • Design scalable inference architectures that support enterprise workloads. • Work with GPU infrastructure, containerized applications, Kubernetes, and cloud platforms. • Collaborate with customer engineering teams to optimize system reliability, latency, scalability, and performance. • Address infrastructure, security, and compliance challenges to ensure successful production deployments. • Present technical recommendations to engineering teams and executive leadership. • Build trusted relationships with customer stakeholders, identify champions, address objections, and drive successful deployments. • Identify recurring customer pain points and provide actionable feedback to internal product and engineering teams. • Influence product roadmap decisions through customer insights and field experience.

• Design, develop, and maintain scalable full-stack applications using Node.js and React.js. • Build and integrate REST APIs and cloud-based solutions. • Work with AWS services, including exposure to AWS Bedrock. • Integrate Generative AI capabilities into applications and contribute to AI-powered features. • Collaborate with cross-functional teams to deliver high-quality software solutions.

• Drive the architecture, design, and engineering solutioning of scalable AI-powered enterprise platforms across EXL’s strategic engagements. • Anchor the technology vision across Data, CX, AI, and Automation layers, supporting both sales pursuits and client delivery. • Lead Deep Tech capability, partner ecosystem and client pursuits.