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, delivery dependencies, and client expectations.
- Design Azure AI and LLM architectures using Azure AI Foundry, Foundry Agent Service, Azure OpenAI, Azure AI Search, API Management, Logic Apps, and Functions.
- Architect model- and tool-agnostic multi-agent systems with orchestration, tool use, memory, context management, 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 covering accuracy, relevance, faithfulness, groundedness, latency, cost, safety, security, and reliability.
- Establish centrally enforced 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 overall experience is stated as required; the detailed qualifications require 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 with 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 industries such as banking, insurance, healthcare, public sector, retail, or energy.
- Experience with 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 designing 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.