Senior Cloud Engineer

Role Overview The Senior Cloud Engineer is a hands-on, client-facing role responsible for designing, building, and implementing enterprise cloud infrastructure, migration and modernization programs, and AI solutions. This role stays technical: the Senior Cloud Engineer builds the Landing Zone, executes the migration, and implements the AI solution, while also carrying the skills and presence of a consultant to advise the client directly and stand behind the work in front of technical and executive stakeholders. As a senior member of the Professional Services team, this position leads client engagements end-to-end: framing the problem, designing and building the solution, presenting it to stakeholders, and staying hands-on through delivery. The role requires both deep technical craft in Landing Zone/networking, migration execution, and AI solution implementation, and the consultative judgment to guide clients through the decisions along the way. Key Responsibilities 1. Cloud Infrastructure & Landing Zone Engineering Design and build enterprise Cloud Landing Zone architecture — account/organization structure, guardrails, network topology, and hybrid connectivity — aligned to the AWS Well-Architected FrameworkImplement network architecture: VPC design, hub-and-spoke/transit gateway topologies, hybrid connectivity (VPN/Direct Connect), DNS, segmentation, and security zoningDefine and implement governance frameworks: IAM/RBAC models, security baselines, and cost-governance guardrails for multi-account environmentsBuild and maintain Infrastructure as Code (Terraform, CloudFormation) to deploy and enforce the agreed architectureProduce and present architecture decision records, HLD/LLD, and as-built documentation to both engineering teams and client executives2. Migration & Modernization Lead migration discovery and assessment using the 7 R's framework, translating findings into a prioritized, business-justified roadmapDevelop migration business cases, TCO models, and executive-ready roadmaps that connect technical plans to cost and riskBuild and operate migration factory tooling (e.g., AWS Transform/MGN, DMS, App2Container) for large-scale, multi-hundred-to-thousand-server programsExecute lift-and-shift migrations and modernization work — containerization, PaaS adoption, database modernization — hands-onOwn cutover execution and post-migration validation, running the runbook from planning through go-live3. AI Solutions Engineering Design and build AI/ML solutions using cloud-native AI services such as AWS Bedrock, from use-case definition through implementationArchitect and implement generative AI solutions — RAG, agentic workflows, model selection and integration, prompt design — with governance and guardrails built in from the outsetLead AI use-case ideation workshops with client stakeholders, translating business problems into feasible, prioritized initiatives4. Consulting & Client Engagement Act as a trusted advisor to client executives and technical leaders across the cloud and AI adoption journey, backing the advice with the credibility of having built it personallyPlan and facilitate technical workshops, architecture design sessions, and migration/AI discovery sessions with senior stakeholdersSupport pre-sales engagements: solution scoping, proposal development, SOW authoring, and technical presentations to prospective clientsDeliver prescriptive, outcome-oriented recommendations that build long-term client trust and expand the advisory relationship over timeTeam Role & Key Contribution Serve as a hands-on technical lead across infrastructure, migration, and AI workstreams within Professional Services — building solutions personally, not only directing othersMentor and develop junior consultants/engineers across the Infra/MM and AI practice areasLead architecture and governance review boards across client engagementsContribute to practice development — methodology, reusable frameworks, and knowledge assets shared across the teamTeamwork & Collaboration Partner with Pre-Sales, Network, Security, DevOps, and Data/AI teams to shape end-to-end client solutionsTranslate business requirements into secure, scalable, and cost-effective cloud and AI recommendationsCoordinate cross-functional delivery and operational handovers between consulting, engineering, and managed-service teamsFoster shared accountability across internal teams and client engagements Required Qualifications Bachelor's degree in Computer Engineering, Computer Science, or a related field5–7+ years in cloud infrastructure/engineering roles, including hands-on production experience building Landing Zone and network environments (AWS or Huawei Cloud primary)Demonstrated experience leading and executing migration assessment and delivery using the 7R framework, including lift-and-shift and modernizationHands-on experience building AI/ML solutions with cloud-native services (e.g., AWS Bedrock), including GenAI/RAG and agentic solution implementationHands-on experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent) for building and deploying infrastructurePrior experience in consulting, pre-sales, or solutions architecture roles, engaging directly with client stakeholdersStrong networking knowledge (TCP/IP, routing, firewall, DNS, hybrid connectivity)Experience developing business cases, TCO models, or executive-facing proposals Preferred Qualifications AWS Certified Solutions Architect (Associate/Professional); AI/ML certification (e.g., AWS Certified AI Practitioner/Machine Learning)Multi-cloud exposure (e.g., Huawei Cloud HCIP/HCIE) an advantage, not a requirementExperience with containers and Kubernetes (EKS or equivalent)Experience in Data Center or Managed Service Provider environmentsTrack record of facilitating technical workshops or architecture design sessions directly with clientsExperience authoring SOWs, proposals, or other consulting deliverables for enterprise clients Consulting Soft Skills Executive presence — able to advise C-level and senior technical stakeholders with equal credibilityStrong consultative mindset: listens first, diagnoses the real problem, and frames options rather than pushing a single answerConfident workshop and discovery-session facilitation, able to build consensus among stakeholders with competing prioritiesStructured communication and storytelling — translates complex cloud/AI concepts into business narratives and executive-ready summariesBusiness acumen — connects technical recommendations to cost, risk, and value outcomesProposal and business-writing skills: SOWs, business cases, and client-ready decksNegotiation and stakeholder management across client and internal delivery teamsComfortable operating with ambiguity, structuring a path forward under time pressureRelationship-building orientation — treats each engagement as the start of an ongoing advisory relationship, not a one-off deliveryCoaching and mentoring mindset toward junior team members