19 hours ago
Pune, IndiaStaff+
Responsibilities
- Define enterprise AI strategies, target-state architectures, reference architectures, modernization opportunities, and investment roadmaps.
- Architect and integrate AWS-native AI platforms using Bedrock, SageMaker, open-source frameworks, and enterprise cloud services.
- Lead architecture for LLM applications, generative AI, agentic systems, RAG, context layers, model platforms, inference, and AI operations.
- Establish identity, authorization, guardrails, prompt-injection defenses, PII protection, audit logging, lineage, governance, and model risk controls.
- Define evaluation and observability practices covering quality, relevance, groundedness, latency, cost, safety, reliability, and production support.
- Establish AI FinOps standards including usage labeling, token budgets, cost planning, alerts, and optimization controls.
- Lead domain architects and senior SMEs and advise executive clients and business leaders on AI transformation.
- Produce and maintain blueprints, ADRs, sequence diagrams, solution patterns, interface specifications, reference architectures, and governance playbooks.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- Minimum 18 years of overall experience is required.
- At least 15 years of overall experience across software engineering, data engineering, AI/ML engineering, cloud architecture, enterprise architecture, or technology leadership is specified in the qualifications.
- At least 8 years of experience designing and deploying enterprise-grade AI, data, analytics, or cloud-native solutions using a cloud vendor.
- At least 2 years of experience with LLM and generative AI solution architecture, including agentic systems, RAG, prompt engineering, model integration, and evaluation.
- At least 2 years of experience architecting and operationalizing LLM-driven applications in enterprise-scale or production environments.
- At least 6 years of experience in engineering, machine learning, deep learning, NLP, data engineering, or large-scale analytical engineering.
- At least 6 years of experience as a machine learning, data, or AI architect designing large-scale analytical engineering solutions.
- Deep hands-on architecture experience with Amazon Bedrock, Bedrock Agents/AgentCore, Knowledge Bases, Bedrock Guardrails, Bedrock model evaluation, SageMaker, Lambda, API Gateway, Step Functions, EventBridge, OpenSearch Serverless/Vector Engine, S3, IAM, VPC, KMS, CloudWatch, CloudTrail, and AWS Well-Architected practices.
- Experience establishing agent registries, certification models, AI control planes, access models, production evaluation stacks, model risk controls, and cross-platform governance.
- Preferred qualifications include AWS certifications, AWS CDK or Terraform, EKS, Amazon Q, private connectivity, landing zones, regulated workloads, enterprise FinOps, open-source AI frameworks, responsible AI, red-teaming, synthetic data, human-in-the-loop review, A/B testing, and industry thought leadership.
Tech Stack
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.