Data Solution & AI

EXL Service - AI & Data Solutions

---

Experience:

13+ Years

Location:

All EXL Location

Work Mode:

Hybrid

Primary Skillset:

1. Excellent communication, presentation, and client-facing skills with the ability to articulate complex technical solutions to both business and technical stakeholders.
2. Strong hands-on experience in building enterprise solution architecture maps, technical blueprints, system workflows, and AI/data platform architectures.
3. Deep expertise in hyperscaler cloud platforms including Microsoft Azure, AWS, and GCP, with hands-on implementation experience in at least two platforms.
4. Strong knowledge of distributed systems, microservices, event-driven architectures, APIs, asynchronous workflows, and scalable enterprise platform design.
5. Hands-on experience with AI/LLM ecosystems including:
   • OpenAI Models: (GPT-4, GPT-4o, Assistants API)
   • Anthropic Claude Models
   • Google Gemini Models
   • Open-source LLMs: (Llama, Mistral, etc.)
   • Multi-model orchestration and routing strategies.
6. Experience designing and integrating Agentic AI solutions, AI orchestration layers, prompt workflows, MCP integrations, fallback logic, and model switching architectures.
7. Strong understanding of Data Management disciplines including Data Governance, Data Quality, Metadata Management, Lineage, Master Data Management, and DataOps.
8. Hands-on programming capability in Python, TypeScript/JavaScript, or Go, including API integrations, orchestration services, automation, and AI-enabled workflows.
9. Experience with Kubernetes, Docker, service mesh technologies, Terraform, Helm, CI/CD pipelines, and modern DevOps/GitOps practices.
10. Strong expertise in observability, monitoring, and enterprise platform operations using tools such as Grafana, Prometheus, OpenTelemetry, ELK Stack, and real-time telemetry frameworks.
11. Experience building presales demos, proof-of-concepts, sandbox environments, and industry-specific AI/data accelerators across Insurance, Healthcare, Banking, and Retail domains.
12. Strong understanding of enterprise security, zero-trust architecture, IAM/RBAC, OAuth2, API security, encryption standards, and compliance frameworks such as HIPAA, GDPR, and SOC2.
13. Ability to work closely with engineering, product, governance, data science, and business teams to drive technical solutioning and delivery alignment.
14. Experience with semantic layers, knowledge graphs, context graphs, metadata-driven architectures, and AI-ready data platform modernization initiatives.
15. Strong leadership, mentoring, troubleshooting, and technical decision-making capability with the ability to guide engineering teams during architecture, implementation, and client engagements.