Senior Technical Consultant - AI Platform Engineer

Role

A Senior Technical Consultant (AI Platform Engineer) who designs and implements enterprise platform solutions across cloud, application, data, infrastructure, and AI workloads. The role leads customer engagements for cloud migration and platform modernization, builds reusable platform patterns and developer tooling, and incorporates AI-assisted development practices while enforcing security, quality, and governance.

Key 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 platform modernization assessments, planning, execution, and transition activities (landing zones, migration waves, cutover plans, operational handoffs).
• Build reusable platform patterns, automation, self-service workflows, developer tooling, and golden paths.
• Drive AI-accelerated development initiatives and organization-wide AI enablement (assessments, pilots, training, playbooks, governance, adoption roadmaps, measurement).
• Use AI coding assistants and agentic development tools for prototyping, coding, testing, debugging, refactoring, and documentation, with human review and engineering standards.
• Develop Infrastructure as Code, CI/CD pipelines, and GitOps workflows; work with containers, Kubernetes, APIs, event-driven systems, observability, and security.
• 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; participate in proposals, estimates, technical presentations, and pre-sales activities.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent experience.
• 8+ years of professional IT experience and 4+ years in cloud/platform engineering, DevOps, automation, or application modernization.
• Hands-on experience with AWS, Azure, and/or Google Cloud.
• Experience delivering cloud migration and modernization initiatives (assessment, planning, dependency analysis, landing zones, migration waves, cutover, 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/programming skills in Python, PowerShell, Bash, or comparable language.
• Practical experience using AI coding assistants or agentic development tools and understanding of LLMs, RAG, agents, vector databases, model APIs, prompt engineering, and AI application integration patterns.
• Ability to review, secure, test, and productionize AI-generated code.
• Relevant professional certifications (examples: CKA/CKAD, AWS Solutions Architect, Azure AI/Solutions Architect, NVIDIA/AI infrastructure certifications).
• 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 (AWS Migration Hub/MGN, Azure Migrate, Google Migration Center, VMware HCX) and practices like GitOps, service mesh, policy-as-code, platform security, observability, or FinOps.

Success Metrics

• Secure, scalable, and reusable platform solutions delivered to customers.
• Successful migration and modernization of customer workloads with clear operational transition.
• Improved engineering productivity through automation, self-service, and responsible AI-assisted development.
• Platform capabilities that support multiple workload types and safe use of AI tools without compromising quality or security.
• Strong customer relationships and reusable knowledge contributions across the practice.

Benefits (India-specific items called out)

• Comprehensive health insurance with options to extend coverage to dependents.
• Paid time off, company holidays, and additional leave benefits per policy.
• Flexible work arrangements and work-life balance support.
• Learning and development opportunities, certification sponsorship, and upskilling.
• Employee wellness initiatives and programs for physical and mental well-being.
• Retirement and statutory benefits in line with India regulations.
• Inclusive, collaborative culture and internal technical labs for hands-on learning.