Senior Technical Consultant - AI Platform Engineer in India at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Technical Consultant - AI Platform Engineer based in India.
This is a senior, hands-on consulting role focused on designing and delivering modern enterprise platforms across cloud, infrastructure, applications, data, and AI workloads.
You will work directly with customers to lead technical discovery, architecture, cloud migration, modernization, and platform engineering initiatives.
The role combines strong DevOps and cloud-native engineering with emerging AI-assisted development practices.
You will build reusable platform capabilities, automation, developer tooling, and self-service workflows that improve engineering productivity at scale.
You will also help organizations adopt generative AI responsibly through assessments, pilots, enablement, governance, and practical implementation.
Success requires balancing rapid innovation with security, reliability, maintainability, cost efficiency, and operational readiness.
This is an opportunity to influence complex transformation programs while mentoring engineers and contributing reusable expertise to a broader technical practice.
- Lead customer workshops, technical discovery sessions, architecture discussions, solution design activities, and technical workstreams.
- Design and implement scalable platforms supporting cloud-native applications, data platforms, infrastructure services, and AI-enabled workloads.
- Lead cloud migration and modernization initiatives from assessment and planning through architecture, execution, validation, transition, and operational handoff.
- Develop migration strategies, cloud landing zones, modernization roadmaps, workload waves, dependency analyses, cutover plans, and transition approaches.
- Build reusable platform patterns, Infrastructure as Code, automation, self-service workflows, developer tooling, and engineering “golden paths.”
- Lead AI-accelerated development initiatives by integrating AI tools and agentic development practices into software development and engineering workflows.
- Support organization-wide AI enablement through assessments, pilots, training, playbooks, governance frameworks, adoption roadmaps, and measurement programs.
- Use AI coding assistants and agentic tools for prototyping, coding, testing, debugging, refactoring, and documentation while applying rigorous human review and engineering standards.
- Develop and maintain CI/CD pipelines, GitOps workflows, cloud automation, containerized environments, and Kubernetes-based solutions.
- Apply cloud-native technologies and architectural patterns involving APIs, event-driven systems, observability, security, and scalable infrastructure.
- Design and integrate AI application patterns involving LLMs, RAG, agents, vector databases, model APIs, and generative AI services.
- Support platform security, governance, reliability, operational readiness, and cost optimization throughout solution delivery.
- Create reusable accelerators, demonstrations, reference architectures, technical documentation, and implementation guidance.
- Mentor engineers and contribute to internal technical communities, knowledge-sharing initiatives, and enablement programs.
- Participate in proposals, solution estimates, technical presentations, and pre-sales activities while helping build strong customer relationships.
- Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent practical experience.
- 8+ years of professional IT experience, including at least 4 years in cloud, platform engineering, DevOps, automation, application modernization, or related fields.
- Hands-on experience with at least one major cloud platform, such as AWS, Microsoft Azure, or Google Cloud.
- Proven experience delivering cloud migration and platform modernization initiatives, including assessments, dependency analysis, landing zones, migration waves, cutovers, and validation.
- Strong experience with Terraform, Bicep, or another Infrastructure as Code technology.
- Practical expertise with CI/CD, containers, Kubernetes, automation, and cloud-native application architectures.
- Strong scripting or programming capabilities using Python, PowerShell, Bash, or a comparable language.
- Hands-on experience using AI coding assistants or agentic development tools and an understanding of responsible AI-assisted engineering practices.
- Knowledge of LLMs, generative AI applications, RAG, prompt engineering, AI agents, and model APIs, with the ability to review, secure, test, and productionize AI-generated code.
- Strong consulting, communication, technical writing, presentation, and customer-facing skills.
- Ability to work effectively with technical and non-technical stakeholders and translate complex requirements into practical solutions.
- Relevant professional certifications are highly valued, including CKA, CKAD, AWS Solutions Architect, AWS AI Practitioner, Azure AI Fundamentals, Azure Solutions Architect Expert, relevant NVIDIA AI or generative AI certifications, or comparable AI architecture credentials.
- Preferred experience with services such as Amazon Bedrock, SageMaker, Azure OpenAI, Microsoft Foundry, or Google Vertex AI.
- Familiarity with AI frameworks including LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, or similar technologies is advantageous.
- Experience with AI development tools such as Cursor, Windsurf, GitHub Copilot, Claude Code, Devin, Amazon Q Developer, or comparable platforms is a plus.
- Experience building developer platforms, platform APIs, self-service portals, reusable engineering accelerators, or internal developer experiences is preferred.
- Familiarity with cloud migration technologies such as AWS Migration Hub/MGN, Azure Migrate, Google Migration Center, VMware HCX, or comparable solutions is valuable.
- Knowledge of GitOps, service mesh, policy-as-code, platform security, observability, or FinOps is an advantage.
- A proactive, collaborative, mentoring-oriented approach with a strong focus on customer outcomes and continuous improvement.
- Comprehensive health insurance, with options to extend coverage to eligible dependents.
- Paid time off, company holidays, and additional leave benefits according to policy.
- Flexible work arrangements designed to support work-life balance.
- Learning and development opportunities focused on continuous upskilling and professional growth.
- Support for certifications, credentials, and technical training.
- Employee wellness initiatives supporting physical and mental well-being.
- Retirement and statutory benefits in accordance with applicable Indian regulations.
- Inclusive, people-first culture emphasizing collaboration, ownership, diverse perspectives, and professional development.
- Opportunities to work with advanced technologies and participate in cross-functional learning initiatives.