3 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Shape enterprise AI strategy and convert business priorities into phased technical roadmaps.
- Lead AI architecture assessments, target-state definitions, gap analyses, platform selections, modernization planning, and implementation sequencing.
- Define Databricks lakehouse-native AI architectures using Mosaic AI, Delta Lake, Unity Catalog, Vector Search, MLflow, model serving, and Databricks workflows.
- Design model- and tool-agnostic multi-agent systems, including orchestration, memory, tool use, agent registries, AI gateways, and control planes.
- Establish context-layer architecture covering knowledge graphs, ontologies, vector search, semantic retrieval, prompt/context assembly, and conversation state.
- Set standards for security, governance, observability, performance, scalability, reliability, identity, authorization, PII protection, guardrails, auditability, and evaluation.
- Drive inference, model routing, fine-tuning, caching, cost-control, and production deployment architecture decisions.
- Produce authoritative architecture blueprints, ADRs, sequence diagrams, design specifications, integration patterns, 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 experience is stated for the project role; the qualifications also specify 12+ years overall technology experience, 8+ years designing enterprise AI/data/analytics/cloud solutions, 6+ years in engineering or machine learning-related work, and 2+ years in LLM and generative AI solution architecture.
- Experience designing and deploying enterprise-grade AI, data, analytics, or cloud-native solutions using at least one cloud vendor.
- Experience with agentic AI, RAG, prompt engineering, model integration, evaluation patterns, and production or enterprise-scale LLM applications.
- Deep experience with Databricks Mosaic AI, Model Serving, Agent Framework, MLflow tracing and evaluation, Vector Search, Unity Catalog, Delta Lake, Delta Live Tables, Lakehouse Monitoring, Feature Store, Databricks Workflows, Jobs, and Model Training.
- Ability to architect RAG, embeddings, vector databases, semantic retrieval, context engineering, multi-agent orchestration, tool calling, memory, model routing, and generative AI evaluation.
- Experience defining non-functional requirements and controls for performance, scalability, security, privacy, governance, observability, resiliency, cost optimization, and operational readiness.
- Ability to compare platforms, frameworks, foundation models, and deployment patterns and make defensible technology recommendations.
- Experience with AI gateway and control-plane patterns, agent registries, certification gates, authorization models, guardrails, model risk controls, and production governance.
- Senior architecture experience in domains such as financial services, healthcare, manufacturing, retail, telecom, or life sciences, plus strong executive stakeholder communication.
- Preferred experience includes Databricks professional certifications, Spark or PySpark, LangGraph, LangChain, LlamaIndex, Haystack, Semantic Kernel, FastAPI, Docker, Kubernetes, responsible AI, model risk management, red-teaming, synthetic data, 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.