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RIS AI Architect Senior Manager

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Onsite

RIS AI Architect Senior Manager

Accenture in India

RIS AI Architect Senior Manager

Skills

Google Cloud PlatformData EngineeringDockerNodePythonJavaC#MicroservicesSpring BootJenkinsSales OpsMachine LearningAIAWSGitHubKubernetesCloud ArchitectComplianceTerraformAzure

3 months ago

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Important information


Contract type:

Permanent

Location:

Pune Division, Maharashtra, India

Work mode:

Onsite

Published on:

25 August 2026

What they need


Project Role Description: Support developing Cloud Native and custom SI solutions powered by AI and cloud-native technologies, support sales teams, perform opportunity triage and sales support liaison, and coordinate with clients on the details of the solution.

Has expertise in one or more public cloud provider technologies (AWS, Azure, GCP) and is capable of embedding these capabilities—alongside AI/ML services such as Generative AI, LLMs, and intelligent automation—into existing or new cloud-based solutions to drive measurable client value.

Must have Skills: AI/ML platforms, Cloud-native architecture, Languages & frameworks(Java / Spring Boot, .NET / C#, Python (primary for AI/ML), Node.js), Microservices.

Good to Have Skills: Responsible AI, Data engineering, Automation, Domain expertise

Key Responsibilities:

  • Lead end-to-end solution architecture for large, complex cloud-native and AI transformation engagements, from discovery to proposal and transition-to-delivery
  • Define reference architectures integrating Generative AI (LLMs, RAG, agents), MLOps pipelines, AIOps, and intelligent automation into enterprise-grade cloud solutions
  • Architect multi-cloud and hybrid solutions across AWS, Azure, and GCP—leveraging platform-native AI services (SageMaker, Azure AI Foundry, Vertex AI) alongside open-source frameworks
  • Drive Application Modernization strategies including cloud-native refactoring, microservices decomposition, API-led integration, event-driven architectures, and serverless paradigms
  • Ensure solutions address non-functional requirements: security, resilience, observability, cost optimization, and responsible AI/governance compliance

Technical Experience:

Deep expertise across AWS, Microsoft Azure, and Google Cloud Platform—services, pricing, well-architected frameworks, and partner programs

Cloud-native architecture: Kubernetes (EKS, AKS, GKE), containerisation (Docker), service mesh (Istio/Linkerd), GitOps, Helm

Infrastructure as Code: Terraform, Pulumi, CDK; CI/CD toolchains: GitHub Actions, Azure DevOps, Jenkins

Private cloud and hybrid architectures: VMware Tanzu, Azure Arc, AWS Outposts, OpenShift

Professional Attributes:

Exceptional executive presence with the ability to engage C-suite stakeholders, translate complex technical concepts, and build long-term client trust

Demonstrated track record of winning large, complex technology deals in a pre-sales / solution architect capacity at a reputed IT services or consulting firm

Outstanding written and oral communication; adept at crafting compelling solution narratives, executive decks, and proposal responses

Strategic thinker with strong business acumen—able to balance technical rigor with commercial pragmatism and client value creation

Collaborative leader who can energise cross-functional pursuit teams, manage ambiguity, and drive decisions at pace

Continuous learner with a passion for emerging AI and cloud technologies; active contribution to thought leadership and community

Educational Qualification:

15+ years of overall IT experience, with a minimum of 5 years in a Solution Architect or Pre-Sales Architect role at a tier-1 IT services or consulting organisation

Proven experience winning and architecting deals in the $5M–$50M+ range across cloud transformation, application modernisation, and AI/data programmes

Mandatory cloud certifications: AWS Solutions Architect – Professional, Azure Solutions Architect Expert, or GCP Professional Cloud Architect (two or more preferred)

AI/ML certifications desirable: AWS ML Specialty, Azure AI Engineer, Google Professional ML Engineer, or equivalent

Bachelor's or Master's degree in Computer Science, Engineering, or a related field

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