Senior Cloud Engineer

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