18 hours ago
Pune, IndiaStaff+
Responsibilities
- Define technical visions, architecture blueprints, non-functional requirements, and implementation roadmaps for enterprise AI systems.
- Design AWS-native generative AI platforms using Bedrock, SageMaker, RAG, agents, vector search, guardrails, identity controls, auditability, and cost controls.
- Architect multi-agent systems with orchestration, tool use, memory, context management, MCP/control-plane patterns, and reusable service abstractions.
- Design data and context layers covering ingestion, preprocessing, chunking, embeddings, vector search, knowledge graphs, and semantic retrieval.
- Define evaluation frameworks for accuracy, relevance, groundedness, latency, cost, safety, security, and operational reliability.
- Establish AI security, governance, observability, prompt-injection defenses, PII protection, access controls, audit logging, and tracing.
- Lead stakeholder workshops, vendor and build-versus-buy evaluations, and communication of architecture trade-offs and risks.
- Maintain architecture decision records, diagrams, design specifications, integration patterns, and reusable reference architecture assets.
Requirements
- At least 12 years of professional experience is required; the qualifications also specify 10+ years in software engineering, data engineering, AI/ML engineering, or technology architecture.
- Bachelor’s degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 5 years designing and deploying enterprise-grade AI or cloud data solutions using a cloud vendor.
- At least 2 years of experience in agentic AI, LLM, and generative AI solution architecture or engineering delivery.
- At least 4 years of coding experience with Python, APIs, distributed systems, reusable frameworks, and cloud-native application patterns.
- At least 4 years of experience in machine learning, deep learning, NLP, data engineering, analytical engineering, or AI product delivery.
- Hands-on experience with AWS AI, data, security, networking, monitoring, and integration services including Bedrock, SageMaker, Lambda, API Gateway, Step Functions, EventBridge, OpenSearch, S3, IAM, VPC, KMS, CloudWatch, and CloudTrail.
- Knowledge of LLM architecture patterns including RAG, embeddings, vector databases, prompt engineering, model routing, fine-tuning, function calling, tool integration, and agent orchestration.
- Experience with reusable agent services, memory services, integration adapters, orchestration layers, evaluation harnesses, deployment pipelines, testing, MLOps/LLMOps, monitoring, and production release governance.
- Experience as a solution or technology architect in banking, insurance, healthcare, retail, telecom, or capital markets.
- Preferred qualifications include AWS certifications, AWS CDK or Terraform, EKS, Bedrock AgentCore, 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, and GenAI FinOps.
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.