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HomeCompaniesFa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2VP of Cloud Engineering, Operations & Delivery

VP of Cloud Engineering, Operations & Delivery

Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 · United States; US New Jersey (JCO) C79 · Remote · Active · Oracle Recruiting Cloud / Fusion HCM

Job facts

FieldValue
CompanyFa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2
TitleVP of Cloud Engineering, Operations & Delivery
Normalized title-
Department / teamGlobal Technology
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time
Salary-
Statusactive
ATS providerOracle Recruiting Cloud / Fusion HCM
Posted / first seen2026-06-09 / 2026-06-10
Changed / last seen2026-06-17 / 2026-06-18

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Linked records

CompanyFa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2
Source907773df-d032-42dc-b60a-978734f5ac21
ATS providerOracle Recruiting Cloud / Fusion HCM

Description

Description 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?" Responsibilities 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-driven insights and autonomous recommendations  Define and enforce observability standards across logging, metrics, and tracing using Datadog and CloudWatch — and explore how agentic monitoring can move teams from alert fatigue to autonomous resolution  Delivery & Execution Lead end-to-end delivery of cloud engineering engagements — from technical discovery and architecture through deployment, cutover, and steady-state operations  Build scalable delivery frameworks, runbooks, and IaC-driven playbooks that can be applied consistently across verticals and client environments — and actively work to make those playbooks AI-executable over time  Proactively identify technical risks and drive resolution before they become client issues  Team Development Build, mentor, and retain a high-performing team of cloud engineers, DevOps engineers, SREs, and delivery managers — cultivating a team culture that embraces AI-augmented workflows as a force multiplier, not a threat  Define clear career ladders, engineering standards, and technical growth paths that attract and retain top talent — including emerging skills in AI/ML infrastructure, prompt engineering, and agentic system design  Foster a culture of engineering excellence, continuous learning, and genuine curiosity about what AI agents can unlock  Executive & Client Engagement Communicate cloud strategy, delivery status, and technical decisions clearly to executive stakeholders — both internally and with clients  Help clients articulate and develop their agentic transformation roadmap — translating the potential of AI agents into concrete, phased business outcomes  Participate in pre-sales and client-facing conversations with enough technical depth to build confidence and credibility  Translate cloud provider roadmaps — including rapidly evolving AI and agent capabilities from AWS, Azure, and GCP — into strategic investments and differentiated service offerings  Represent the engineering organization in leadership discussions, helping align technical capabilities with business growth objectives Qualifications 12+ years of experience in cloud infrastructure, platform engineering, or DevOps — with at least 4 years in a senior leadership capacity  Strong working knowledge of AWS, Azure, and GCP — you understand how these platforms work in practice, not just in principle; professional-level certifications are a plus  Solid, proven experience with Infrastructure as Code — particularly Terraform — including best practices around module design, state management, GitOps workflows, and policy enforcement  Demonstrated experience leading cloud delivery programs for enterprise clients across multiple industries  Practical exposure to AI agents and agentic frameworks — you've either built, deployed, or operated AI agent systems in a production or near-production context and understand how to design reliable, governed agentic workflows  A creative, process-transformation mindset — you look at how work gets done today and can credibly envision how intelligent agents could do it better, faster, and more reliably tomorrow  Working knowledge of Kubernetes in production environments and modern CI/CD practices  Familiarity with cloud security frameworks and compliance requirements relevant to multi-vertical client environments  A track record of building and developing high-performing engineering teams  Exceptional communication skills — able to engage engineers at a technical level and translate that into clear, confident messaging for executives and clients alike Preferred Qualifications Hands-on experience with agentic AI platforms such as LangGraph, AutoGen, Amazon Bedrock Agents, Azure AI Agent Service, or Vertex AI Agent Builder   Experience designing multi-agent architectures — including agent orchestration, tool use, memory management, and human-in-the-loop design patterns  Familiarity with LLM integration patterns in cloud-native applications — RAG pipelines, vector databases, embedding workflows, and model hosting on cloud infrastructure  Experience in a managed services or solutions provider environment serving diverse industry verticals  Background in platform engineering or Internal Developer Platform (IDP) development  Familiarity with policy-as-code tools such as OPA, Sentinel, or Checkov  AWS, Azure, and/or GCP professional-level certifications, including any AI/ML specialty certifications

Full job record

Job ID211b9d6270e87dee0ebb5e8696ede7cbc91b0970
Org ID3ea3b397-9a23-408a-8421-50fd1d902746
Source ID907773df-d032-42dc-b60a-978734f5ac21
Board ID907773df-d032-42dc-b60a-978734f5ac21
Provideroracle_hcm
Provider Job Key15322
TitleVP of Cloud Engineering, Operations & Delivery
Normalized Title
Statusactive
Activeyes
Location TextUnited States; US New Jersey (JCO) C79
DepartmentGlobal Technology
Team
Employment Typefull_time
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
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Salary RawDescription 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?" Responsibilities 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-driven insights and autonomous recommendations  Define and enforce observability standards across logging, metrics, and tracing using Datadog and CloudWatch — and explore how agentic monitoring can move teams from alert fatigue to autonomous resolution  Delivery & Execution Lead end-to-end delivery of cloud engineering engagements — from technical discovery and architecture through deployment, cutover, and steady-state operations  Build scalable delivery frameworks, runbooks, and IaC-driven playbooks that can be applied consistently across verticals and client environments — and actively work to make those playbooks AI-executable over time  Proactively identify technical risks and drive resolution before they become client issues  Team Development Build, mentor, and retain a high-performing team of cloud engineers, DevOps engineers, SREs, and delivery managers — cultivating a team culture that embraces AI-augmented workflows as a force multiplier, not a threat  Define clear career ladders, engineering standards, and technical growth paths that attract and retain top talent — including emerging skills in AI/ML infrastructure, prompt engineering, and agentic system design  Foster a culture of engineering excellence, continuous learning, and genuine curiosity about what AI agents can unlock  Executive & Client Engagement Communicate cloud strategy, delivery status, and technical decisions clearly to executive stakeholders — both internally and with clients  Help clients articulate and develop their agentic transformation roadmap — translating the potential of AI agents into concrete, phased business outcomes  Participate in pre-sales and client-facing conversations with enough technical depth to build confidence and credibility  Translate cloud provider roadmaps — including rapidly evolving AI and agent capabilities from AWS, Azure, and GCP — into strategic investments and differentiated service offerings  Represent the engineering organization in leadership discussions, helping align technical capabilities with business growth objectives Qualifications 12+ years of experience in cloud infrastructure, platform engineering, or DevOps — with at least 4 years in a senior leadership capacity  Strong working knowledge of AWS, Azure, and GCP — you understand how these platforms work in practice, not just in principle; professional-level certifications are a plus  Solid, proven experience with Infrastructure as Code — particularly Terraform — including best practices around module design, state management, GitOps workflows, and policy enforcement  Demonstrated experience leading cloud delivery programs for enterprise clients across multiple industries  Practical exposure to AI agents and agentic frameworks — you've either built, deployed, or operated AI agent systems in a production or near-production context and understand how to design reliable, governed agentic workflows  A creative, process-transformation mindset — you look at how work gets 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Salary Min
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Source URLhttps://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/15322
Apply URLhttps://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/15322
First Seen At2026-06-10 11:21:19Z
Last Seen At2026-06-18 12:01:14Z
Last Checked At2026-06-18 12:01:14Z
Last Changed At2026-06-17 11:28:13Z
Inactive At
Source Posted At2026-06-09 16:26:37Z
Source Updated At
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GET https://api.bluedoor.sh/job-postings/v1/orgs/3ea3b397-9a23-408a-8421-50fd1d902746JSON
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