3 days ago
Bengaluru, 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 client-facing expectations.
- Define Azure AI and LLM architectures using Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Logic Apps, API Management, and related Azure services.
- Architect multi-agent systems covering orchestration, tool use, memory, context management, MCP/control-plane patterns, and reusable service abstractions.
- Design data and context layers for ingestion, preprocessing, embeddings, vector search, knowledge graphs, and semantic retrieval.
- Define evaluation frameworks for accuracy, relevance, faithfulness, groundedness, latency, cost, safety, security, and reliability.
- Establish AI security, governance, observability, guardrails, prompt-injection defense, PII protection, access control, audit logging, and tracing controls.
- Maintain architecture decision records, component and sequence diagrams, design specifications, integration patterns, and reusable reference architecture assets.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 12 years of professional experience is stated in the project role description; the qualifications section also specifies 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.
- 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 ML, deep learning, NLP, data engineering, analytical engineering, or AI product delivery.
- Demonstrated solution or technology architecture experience in banking, insurance, healthcare, public sector, retail, or energy.
- Hands-on experience with Microsoft Foundry/Azure AI Foundry, Foundry Agent Service, Azure OpenAI, Azure AI Search, Prompt Flow, Azure Functions, Logic Apps, API Management, Event Grid, Microsoft Fabric, Entra ID, Key Vault, Azure Monitor, and Application Insights.
- Knowledge of LLM architecture patterns including RAG, embeddings, vector databases, prompt engineering, model routing, fine-tuning or adaptation, function calling, tool integration, and agent orchestration.
- Experience defining enterprise AI platform patterns for performance, scalability, security, reliability, observability, governance, cost optimization, and operational support.
- Experience building reusable agent services, memory services, API gateways, integration adapters, orchestration layers, evaluation harnesses, and deployment pipelines.
- Experience with CI/CD, infrastructure-as-code, automated testing, model evaluation, MLOps/LLMOps, monitoring, and production release governance.
- Strong stakeholder management and communication skills for explaining architecture trade-offs, risks, and recommendations to engineering, product, security, and leadership teams.
- Preferred qualifications include Azure Solutions Architect Expert, Azure AI Engineer Associate, or Azure Developer certification experience; Microsoft Fabric, Semantic Kernel, Prompt Flow, private endpoints, Defender for Cloud, Microsoft 365 Copilot, and Responsible AI controls.
- Preferred experience includes LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, MLflow, FastAPI, Docker, Kubernetes, responsible AI, model risk management, AI governance, 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.