Senior Technical Consultant - AI Platform Engineer
New
A
AHEADCloud and AI
India; Gurugram, HaryanaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of professional IT experience; 4+ years in cloud, platform engineering, DevOps, automation, or application modernization
- Required Skills
- AWSPythonGCPKubernetesAzureCI/CDDevOpsTerraformGenerative AI
Requirements
- 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.
- 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.
- One or more relevant professional certifications (e.g., CKA, CKAD, AWS/Azure/NVIDIA AI certifications).
- Strong consulting, communication, technical writing, and customer-facing skills.
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.
- 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 and engineering workflows.
- Use AI coding assistants and agentic development tools for prototyping, coding, testing, debugging, refactoring, and documentation.
- Develop Infrastructure as Code, CI/CD pipelines, GitOps workflows, and cloud automation.
- Support platform security, governance, reliability, operational readiness, and cost optimization.
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