• Get up to speed on the full platform — all VDC workloads, dependencies, and risk areas. Much of this will happen through code, docs, and conversations rather than direct environment access. • Work with SMEs across the org to fill knowledge gaps and build onboarding material for the team. • Write and maintain runbooks, architecture docs, and operational guides. • Design infrastructure for high availability and fault tolerance on Azure (including Azure Government). • Define SLIs, SLOs, and error budgets where none exist today. • Run incident response and blameless postmortems. Turn incidents into improvements. • Identify reliability risks across modern and legacy workloads and build practical remediation plans that work within compliance constraints. • Close observability gaps — define instrumentation requirements and drive implementation. • Set alerting, telemetry, and monitoring standards with partner teams. • Build automation to reduce toil and support fleet management. • Participate in on-call rotations. • Work with IaC, CI/CD, deployment automation, and config management — including in air-gapped or compliance-restricted environments. • Build and maintain testing, canary deployment, and release validation pipelines. • Integrate chaos engineering and monitoring tools, adapting choices to meet regulatory requirements. • Work across product, platform, security, legal, compliance, and operations teams. • Own problems end-to-end — identify gaps, drive solutions, don't wait for direction. • Mentor other engineers and help spread SRE practices across the org.

Role Description The Forward Deployment Engineer (FDE) is the tip-of-the-spear technical role responsible for ensuring that EXLdata.ai is successfully deployed, adopted, and scaled within client environments. You will work side-by-side with client teams, product engineering, and our GenAI agent teams to: - Deploy EXLdata.ai into client cloud infrastructure (AWS/Azure/GCP) - Resolve infra, security, and data pipeline issues in real time - Customize accelerators and agent workflows for client-specific needs - Drive measurable value realization from Day 1 - Champion product enhancements back to the EXLdata.ai engineering team - Deliver white-glove support for clients using our managed platform offering This role is ideal for a senior data engineer who loves solving real-world problems, can operate in ambiguous conditions, learns fast, and thrives in high-impact client environments. Company Description EXLdata.ai is EXL’s flagship multi-agent orchestration platform that automates the end-to-end lifecycle of enterprise data pipelines – spanning data migration, data engineering, data quality, data governance, data ops, and unstructured data annotation. Having launched our MVP and now expanding across multiple Fortune-500 engagements, we are entering a rapid scale-up phase with two distinct delivery models: - Client-Deployed Model: Deploy EXLdata.ai within the client’s own cloud (AWS/Azure/GCP) and orchestrate their pipelines using our accelerator suite. - Managed Platform Model: EXL hosts EXLdata.ai in a dedicated private cloud and provides a white-glove, Data-Product-as-a-Service experience. To support this growth, we are hiring a Forward Deployment Engineer who will serve as the technical anchor at the intersection of cloud engineering, data engineering, GenAI, and client value realization.

• Build and automate stable, maintainable infrastructure landscapes • Operate, evolve and secure multiple Kubernetes clusters • Manage our Linux systems (physical servers, VMs, NAS) • Automate deployment, operations and maintenance processes • Implement Security-by-Design in code: system hardening, access control, secrets management, logging & monitoring • Translate C5, ISO 27001 and ISO 27018 requirements into technical controls — closely coordinated with our internal Information Security Management (ISMS) • 2nd-level incident handling (analysis & remediation) • Help define infrastructure standards from the outset

• Own and improve AWS infrastructure across staging and production environments • Build, maintain, and standardize Infrastructure-as-Code using Terraform • Manage and optimize containerized workloads on ECS Fargate • Strengthen observability: metrics, dashboards, alerting, and logging • Improve CI/CD pipelines using GitHub Actions • Enhance IAM, secrets management, and overall cloud security posture • Perform maintenance of databases running on RDS • Support backend teams with debugging or small changes in Node.js/NestJS • Drive automation, reliability, and scalability across the platform