19 hours ago
Pune, IndiaStaff+
Responsibilities
- Translate business strategy and product goals into technical visions, architecture blueprints, non-functional requirements, and implementation roadmaps.
- Lead stakeholder workshops covering feasibility, scope, solution boundaries, dependencies, and delivery expectations.
- Design AWS-native generative AI platforms using Bedrock, SageMaker, S3, Knowledge Bases, OpenSearch, RAG, agent patterns, guardrails, identity controls, auditability, token budgets, and cost controls.
- Architect model- and tool-agnostic multi-agent systems with orchestration, tool use, memory, context management, MCP/control-plane patterns, and reusable service abstractions.
- Design data and context layers for ingestion, preprocessing, synchronization, chunking, embeddings, vector search, knowledge graphs, and semantic retrieval.
- Define evaluation frameworks for accuracy, relevance, faithfulness, groundedness, latency, cost, safety, security, and operational reliability.
- Establish AI security, governance, and observability controls including prompt-injection defense, PII protection, access control, audit logging, and tracing.
- Maintain architecture decision records, diagrams, design specifications, integration patterns, and reusable reference architecture assets.
Requirements
- A bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline is required.
- At least 12 years of experience is required, with at least 10 years in software engineering, data engineering, AI/ML engineering, or technology architecture.
- At least 5 years of experience designing and deploying enterprise-grade advanced AI or cloud data solutions using a cloud vendor is required.
- At least 2 years of experience in agentic AI, LLM, and generative AI solution architecture or engineering delivery is required.
- At least 4 years of coding experience with Python, APIs, distributed systems, reusable frameworks, and cloud-native application patterns is required.
- At least 4 years of experience in ML, deep learning, NLP, data engineering, analytical engineering, or AI product delivery is required.
- Demonstrated experience as a solution or technology architect in industries such as banking, insurance, healthcare, retail, telecom, or capital markets is required.
- Hands-on experience with AWS Bedrock, Bedrock Agents or AgentCore, Knowledge Bases, Guardrails, SageMaker, Lambda, API Gateway, Step Functions, EventBridge, OpenSearch, S3, IAM, VPC, KMS, CloudWatch, and CloudTrail is required.
- Strong knowledge of LLM architecture patterns, including RAG, embeddings, vector databases, prompt engineering, model routing, fine-tuning, function calling, tool integration, and agent orchestration is required.
- Experience with reusable agent services, memory services, API gateways, integration adapters, orchestration layers, evaluation harnesses, deployment pipelines, automated testing, MLOps/LLMOps, monitoring, and production release governance is required.
- Preferred qualifications include AWS architecture or machine learning certifications; AWS CDK or Terraform; EKS; Amazon Q; private connectivity; regulated workload architecture; open-source AI frameworks; responsible AI; model risk management; red-teaming; human-in-the-loop review; A/B testing; GenAI FinOps; and enterprise reference architecture development.
- Strong stakeholder management and communication skills are preferred for explaining architecture trade-offs, risks, and recommendations to engineering, product, security, and leadership teams.
Tech Stack
Categories
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.