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 Framework
- Implement network architecture: VPC design, hub-and-spoke/transit gateway topologies, hybrid connectivity (VPN/Direct Connect), DNS, segmentation, and security zoning
- Define and implement governance frameworks: IAM/RBAC models, security baselines, and cost-governance guardrails for multi-account environments
- Build and maintain Infrastructure as Code (Terraform, CloudFormation) to deploy and enforce the agreed architecture
- Produce and present architecture decision records, HLD/LLD, and as-built documentation to both engineering teams and client executives
2. Migration & Modernization
- Lead migration discovery and assessment using the 7 R's framework, translating findings into a prioritized, business-justified roadmap
- Develop migration business cases, TCO models, and executive-ready roadmaps that connect technical plans to cost and risk
- Build and operate migration factory tooling (e.g., AWS Transform/MGN, DMS, App2Container) for large-scale, multi-hundred-to-thousand-server programs
- Execute lift-and-shift migrations and modernization work — containerization, PaaS adoption, database modernization — hands-on
- Own cutover execution and post-migration validation, running the runbook from planning through go-live
3. AI Solutions Engineering
- Design and build AI/ML solutions using cloud-native AI services such as AWS Bedrock, from use-case definition through implementation
- Architect and implement generative AI solutions — RAG, agentic workflows, model selection and integration, prompt design — with governance and guardrails built in from the outset
- Lead AI use-case ideation workshops with client stakeholders, translating business problems into feasible, prioritized initiatives
4. 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 personally
- Plan and facilitate technical workshops, architecture design sessions, and migration/AI discovery sessions with senior stakeholders
- Support pre-sales engagements: solution scoping, proposal development, SOW authoring, and technical presentations to prospective clients
- Deliver prescriptive, outcome-oriented recommendations that build long-term client trust and expand the advisory relationship over time
Team 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 others
- Mentor and develop junior consultants/engineers across the Infra/MM and AI practice areas
- Lead architecture and governance review boards across client engagements
- Contribute to practice development — methodology, reusable frameworks, and knowledge assets shared across the team
Teamwork & Collaboration
- Partner with Pre-Sales, Network, Security, DevOps, and Data/AI teams to shape end-to-end client solutions
- Translate business requirements into secure, scalable, and cost-effective cloud and AI recommendations
- Coordinate cross-functional delivery and operational handovers between consulting, engineering, and managed-service teams
- Foster shared accountability across internal teams and client engagements
Required Qualifications
- Bachelor's degree in Computer Engineering, Computer Science, or a related field
- 5–7+ 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 modernization
- Hands-on experience building AI/ML solutions with cloud-native services (e.g., AWS Bedrock), including GenAI/RAG and agentic solution implementation
- Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, or equivalent) for building and deploying infrastructure
- Prior experience in consulting, pre-sales, or solutions architecture roles, engaging directly with client stakeholders
- Strong 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 requirement
- Experience with containers and Kubernetes (EKS or equivalent)
- Experience in Data Center or Managed Service Provider environments
- Track record of facilitating technical workshops or architecture design sessions directly with clients
- Experience 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 credibility
- Strong consultative mindset: listens first, diagnoses the real problem, and frames options rather than pushing a single answer
- Confident workshop and discovery-session facilitation, able to build consensus among stakeholders with competing priorities
- Structured communication and storytelling — translates complex cloud/AI concepts into business narratives and executive-ready summaries
- Business acumen — connects technical recommendations to cost, risk, and value outcomes
- Proposal and business-writing skills: SOWs, business cases, and client-ready decks
- Negotiation and stakeholder management across client and internal delivery teams
- Comfortable operating with ambiguity, structuring a path forward under time pressure
- Relationship-building orientation — treats each engagement as the start of an ongoing advisory relationship, not a one-off delivery
- Coaching and mentoring mindset toward junior team members
