Note: The job is a remote job and is open to candidates in USA. EXL is a company focused on delivering AI consulting and engineering solutions. They are seeking a Senior Consultant to lead the technical relationship with clients, ensuring the delivery of enterprise-grade Generative and Agentic AI systems that provide measurable ROI and governance.
Responsibilities
- Partner with sales and practice leaders to shape pursuits, solution complex deals, and influence SOWs, estimates, and delivery approach
- Serve as the senior technical voice in client pursuits and executive conversations, converting technical credibility into won and expanded engagements
- Build reusable accelerators, reference architectures, and IP that lower delivery cost and differentiate EXL in the market
- Identify expansion opportunities within accounts and translate delivered outcomes into follow-on pipeline
- Lead and grow global, multi-disciplinary AI teams, and raise the technical bar across the practice
- Partner with business and technology leaders to define AI roadmaps and implementation strategy
- Mentor architects and engineers, and build a bench of senior technical talent
- Translate complex architectures for executive and non-technical audiences
- Own architecture, design, and implementation of enterprise-grade GenAI and Agentic AI solutions from concept to production
- Define scalable reference architectures and design patterns for AI platforms, copilots, and intelligent agents
- Establish architectural standards, reusable components, and best practices across delivery programs
- Design secure, resilient, highly available AI systems at enterprise scale, across structured and unstructured data
- Design and deliver LLM-powered applications: conversational AI, enterprise copilots, knowledge management, and workflow automation
- Architect advanced retrieval using RAG, Agentic RAG, Graph RAG, knowledge-graph, and hybrid approaches
- Design multi-agent systems with modern orchestration and reasoning architectures, including human-in-the-loop and autonomous frameworks
- Define memory, context, planning, tool-use, and reasoning strategies for agentic systems
- Stay technical. Contribute to architecture, critical-path code, design reviews, and the hardest technical problems
- Design APIs, microservices, and cloud-native AI services that underpin enterprise AI ecosystems
- Guide teams on software architecture, performance, scalability, security, and maintainability
- Architect governance frameworks for auditability, observability, explainability, and compliance
- Design guardrails for hallucination, prompt injection, toxicity, and model safety
- Establish LLMOps: evaluation pipelines, automated testing, CI/CD, monitoring, and production governance
- Define evaluation frameworks spanning quality, safety, reliability, latency, and business outcomes
Skills
- 10–15 years across software engineering, AI/ML, data science, or enterprise architecture, with a clear trajectory into senior technical leadership
- Proven track record architecting and deploying production-scale AI, from strategy through implementation
- Experience in a consulting, services, or client-facing delivery environment, including supporting pre-sales or solution shaping
- Experience leading globally distributed, multi-disciplinary teams
- Bachelor's in Computer Science, AI, Engineering, Data Science, or a related field
- Expert Python; REST APIs and microservices; FastAPI; distributed systems; cloud-native architecture
- Deep experience with one of Azure, OpenAI, AWS Bedrock, Claude; Kubernetes and cloud-native deployment
- CI/CD for AI, automated evals, experiment tracking, observability, model lifecycle management
- Governance frameworks, guardrails, model safety, compliance, and auditability
- Master's in Computer Science, AI, Engineering, Data Science, or a related field
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