VP of Cloud Engineering, Operations & Delivery
EXLAbout the role
Remote Role
Base Salary 200-225k plus 20% bonus and performance equity
About the Role
We are seeking an experienced and well-rounded VP of Cloud Engineering, Operations & Delivery to lead our cloud practice across a diverse portfolio of industry verticals. This role sits at the intersection of technical authority, executive leadership, and forward-thinking innovation — someone who brings genuine cloud engineering depth, while also driving strategy, client relationships, and organizational growth.
You will lead high-performing teams delivering complex, multi-cloud solutions across AWS, Azure, and Google Cloud Platform, setting the technical bar while ensuring the business delivers on its commitments. Critically, you will help shape and lead our evolution into an agentic AI-powered future — identifying opportunities to transform how our teams and our clients design, deploy, operate, and optimize cloud infrastructure using AI agents and intelligent automation.
The ideal candidate is a natural communicator who can shift seamlessly from an architecture discussion with engineers to a strategic briefing with a client's executive team — and be credible in both rooms. They are also someone who looks at today's manual, repetitive, or complex processes and asks: "How do we let intelligent agents handle this?"
Key Responsibilities
Technical Leadership
- Serve as the senior technical authority for cloud architecture and infrastructure decisions across AWS, Azure, and GCP
- Advance and mature our Infrastructure as Code (IaC) practices — Github, Jenkins, Terraform, Qualys, Sonarqube, etc. — ensuring consistency, security, and scalability across client environments
- Provide meaningful technical guidance and architectural direction to engineering teams — going beyond high-level oversight to engage substantively on design decisions, standards, and delivery quality
- Guide adoption of cloud-native patterns including Kubernetes (EKS/AKS/GKE), serverless, CI/CD automation, and event-driven architecture
- Lead architecture reviews and serve as the escalation point for complex technical challenges
- Ensure security and compliance are embedded into infrastructure from the ground up — spanning IAM design, network segmentation, secrets management, and frameworks such as SOC 2, NIST, CIS, HIPAA, and PCI-DSS
Agentic AI Strategy & Transformation
- Champion the adoption of AI agents and multi-agent systems to transform how cloud infrastructure is built, operated, and optimized — moving teams from reactive, manual workflows to intelligent, autonomous execution
- Identify high-value opportunities to introduce agentic workflows into engineering operations — including infrastructure provisioning, incident detection and remediation, cost optimization, compliance monitoring, security response, and deployment pipelines
- Lead the evaluation and adoption of agentic AI frameworks and platforms (e.g., LangGraph, AutoGen, Amazon Bedrock Agents, Azure AI Agent Service, Vertex AI Agent Builder) to build purpose-built agents that extend the capabilities of our engineering teams
- Define governance, guardrails, and human-in-the-loop checkpoints for agentic systems operating in cloud environments — ensuring autonomous actions are safe, auditable, and aligned with client expectations
- Collaborate with engineering and solutions teams to design agentic delivery pipelines — where AI agents assist in code generation, IaC validation, drift detection, security scanning, and release orchestration
- Work with peer technology teams to identify process transformation opportunities — helping envision, roadmap and execute an agentic future state for cloud operations and engineering workflows
- Stay ahead of the rapidly evolving AI agent ecosystem and bring informed, practical perspectives on what is production-ready versus experimental
Operations & Reliability
- Own the operational health of cloud environments across the client portfolio — including availability, performance, security posture, and cost efficiency
- Mature SRE practices across the organization: SLOs, error budgets, incident management, and blameless postmortems
- Drive FinOps discipline — optimizing cloud spend through right-sizing, commitment strategies, tagging governance, and anomaly detection — increasingly augmented by AI-drive
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