Senior Technical Consultant - AI Platform Engineer
We are seeking a hands-on Senior Technical Consultant to design and implement enterprise platform solutions across cloud, application, data, infrastructure, and AI workloads. This role combines strong platform engineering fundamentals with modern AI-assisted development practices. The consultant will lead cloud migration and cloud platform modernization initiatives, work directly with customers, lead technical workstreams, build reusable platform capabilities, and use AI coding tools and vibe coding techniques to accelerate solution delivery while maintaining high standards for security, quality, reliability, and governance.
Responsibilities
Lead customer workshops, technical discovery, architecture
discussions, and solution design.
Design and implement scalable platforms for cloud-native
applications, data platforms, infrastructure services, and AI
enabled workloads.
Lead cloud migration and cloud platform modernization
assessments, planning, architecture, execution, and transition
activities.
Design migration strategies, landing zones, modernization
roadmaps, workload waves, cutover plans, and operational
handoffs.
Build reusable platform patterns, automation, self-service
workflows, developer tooling, and golden paths.
Lead AI-accelerated development initiatives that integrate AI tools
into customer software development lifecycles, engineering
workflows, and delivery practices.
Drive organization-wide AI enablement for customers through
assessments, pilots, training, playbooks, governance, adoption
roadmaps, and measurement frameworks.
Use AI coding assistants and agentic development tools for
prototyping, coding, testing, debugging, refactoring, and
documentation.
Apply human review and engineering standards to validate AI
generated code and solutions.
Develop Infrastructure as Code, CI/CD pipelines, GitOps
workflows, and cloud automation.
Work with containers, Kubernetes, APIs, event-driven systems,
observability, security, and cloud-native architectures.
Understand LLM, RAG, agent, vector database, model API, and AI
application integration patterns.
Support platform security, governance, reliability, operational
readiness, and cost optimization.
Create reusable accelerators, technical documentation,
demonstrations, and reference architectures.
Mentor engineers and contribute to internal technical communities
and enablement.
Participate in proposals, estimates, technical presentations, and
pre-sales activities.
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, Information
Technology, or equivalent practical experience.
8+ years of professional IT experience.
4+ years of experience in cloud, platform engineering, DevOps,
automation, application modernization, or related areas.
Hands-on experience with AWS, Azure, and/or Google Cloud.
Experience delivering cloud migration and cloud platform
modernization initiatives, including assessment, planning,
dependency analysis, landing zones, migration waves, cutover, and
validation.
Experience with Terraform, Bicep or another Infrastructure as
Code technology.
Experience with CI/CD, containers, Kubernetes, automation, and
cloud-native application patterns.
Strong scripting or programming skills in Python, PowerShell,
Bash, or a comparable language.
Practical experience using AI coding assistants or agentic
development tools.
Understanding of LLMs, generative AI applications, RAG, prompt
engineering, agents, and model APIs.
Ability to review, secure, test, and productionize AI-generated
code.
One or more relevant professional certifications, such as:
Certified Kubernetes Administrator (CKA) or Certified
Kubernetes Application Developer (CKAD).
AWS Certified Solutions Architect - Associate or Professional.
AWS Certified AI Practitioner.
Microsoft Certified: Azure AI Fundamentals or Microsoft
Certified: Azure Solutions Architect Expert.
Relevant NVIDIA AI, Generative AI, or AI infrastructure
certification.
Claude Certified Architect or an equivalent AI architecture
certification.
Strong consulting, communication, technical writing, and
customer-facing skills.
Preferred Qualifications
Experience with Amazon Bedrock, SageMaker, Azure OpenAI,
Microsoft Foundry, or Google Vertex AI.
Experience with LangChain, LangGraph, LlamaIndex, Semantic
Kernel, CrewAI, or similar frameworks.
Experience with Cursor, Windsurf, GitHub Copilot, Claude Code,
Devin, Amazon Q Developer, or similar tools.
Experience building developer platforms, platform APIs, self
service portals, or reusable engineering accelerators.
Experience with cloud migration tools such as AWS Migration Hub
or MGN, Azure Migrate, Google Migration Center, VMware HCX,
or comparable technologies.Experience with GitOps, service mesh, policy-as-code, platform
security, observability, or FinOps.
Cloud, Kubernetes, Terraform, DevOps, AI, or security
certifications.
What Success Looks like:
Customers receive secure, scalable, and reusable platform
solutions.
Customers successfully migrate and modernize workloads and
cloud platforms with clear transition and operational plans.
Engineering teams improve productivity through automation, self
service, and responsible AI-assisted development.
Platform capabilities support multiple workload types rather than
only AI workloads.
AI tools are used to accelerate delivery without compromising
quality, security, or maintainability.
The consultant builds strong customer relationships and
contributes reusable knowledge to the broader practice.