18 hours ago
Pune, IndiaStaff+
Responsibilities
- Design and deliver end-to-end AI platform architectures on Databricks across classical machine learning, generative AI, LLM applications, RAG, agentic workflows, and enterprise integrations.
- 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, delivery expectations, and architecture trade-offs.
- Design lakehouse-centric LLM architectures, governed RAG and agent systems, model-serving deployments, evaluation standards, monitoring, and auditable production workflows.
- 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 covering 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 guardrails, prompt-injection defense, PII protection, access control, audit logging, and tracing.
- Maintain architecture decision records, component and sequence diagrams, design specifications, integration patterns, and reusable reference architectures.
Requirements
- Minimum 12 years of experience is required.
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 10 years of experience in software engineering, data engineering, AI/ML engineering, or technology architecture.
- At least 5 years designing and deploying enterprise-grade AI or cloud data solutions using at least one 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.
- Demonstrated experience as a solution or technology architect in industries such as financial services, healthcare, manufacturing, retail, telecom, or life sciences.
- Hands-on 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.
- Strong knowledge of LLM architecture patterns including RAG, embeddings, vector databases, prompt engineering, model routing, fine-tuning, 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 infrastructure-as-code, automated testing, model evaluation, MLOps/LLMOps, monitoring, CI/CD, and production release governance.
- Strong stakeholder management and communication skills for working with engineering, product, security, and leadership teams.
- Preferred experience includes Databricks professional certifications, Spark/PySpark, Unity Catalog governance, Delta Live Tables, MLflow, LangGraph/LangChain, model fine-tuning, and lakehouse cost or performance optimization.
- Preferred exposure includes LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, MLflow, FastAPI, Docker, Kubernetes, 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.