Project Role: Data Science PractitionerProject Role Description Formulating, design and deliver AI/ML-based decision-making frameworks and models for business outcomes. Measure and justify AI/ML based solution values.

Must Have Skills

- Data Science

Valuable to Have Skills

- NA

Minimum Experience

- Minimum 12 year(s) of experience is required

Educational Qualification

- 15 years full time education

AI Engineering Lead / Solution Architect - Knowledge Graph & Agentic AIExperience

- 12 years overall, including 5 years hands-on in production GenAI/Agentic AI

Location

- India

Role Summary Own enterprise AI architecture and platform strategy for agentic, multi-agent, and knowledge-graph-backed systems. Lead the full AI lifecycle - use-case discovery, architecture, engineering, governance, security, and production optimization - while mentoring engineering teams and representing architecture decisions to senior stakeholders.

Key Responsibilities

- Define enterprise AI/agentic architecture standards, security, governance, and observability frameworks across engagements
- Lead design reviews for GenAI, RAG, and multi-agent solutions, from high-level architecture through detailed design
- Architect and oversee production-grade agentic/multi-agent AI platforms (e.g., CrewAI, LangGraph, or equivalent orchestration frameworks) supporting high-concurrency, low-latency enterprise workloads
- Design and integrate knowledge graph/semantic layer components (e.g., Neo4j or equivalent) for retrieval, reasoning, and data grounding across agentic workflows
- Build reusable AI platform capabilities - LLMOps, model evaluation, and observability practices - and drive enterprise adoption roadmaps
- Own responsible-AI, security (RBAC, SSO, audit logging, encryption), and compliance posture for regulated-industry deployments
- Mentor AI engineers/architects on agentic AI, RAG, and cloud AI engineering practices




- Partner with client/executive stakeholders to translate business priorities into an AI delivery roadmap
- Champion technical innovation and reusable frameworks across the AI engineering practice

Required Skills & Experience

- 12 years in software/AI engineering, with 5 years hands-on in production GenAI, RAG, and agentic/multi-agent systems
- LLM engineering: GPT/Claude/LLaMA-class models, prompt engineering, function/tool calling, RAG architecture
- Agentic AI frameworks (e.g., CrewAI, LangGraph, or equivalent) working knowledge of agent-to-agent and tool-calling protocols (e.g., MCP, A2A)
- Hands-on depth with Azure AI and integration services - Azure AI Foundry, Azure Functions, Azure Logic Apps - or equivalent AWS/GCP AI and serverless stacks
- Knowledge graph/semantic technologies - Neo4j or equivalent, graph-based retrieval and ontology patterns
- Strong programming: Python, TypeScript/Node.js, FastAPI, React.js, SQL
- Data layer: PostgreSQL, MongoDB, and cloud-native relational/NoSQL stores, plus vector/AI-search indexing
- AI evaluation and observability practices for production LLM systems
- Track record owning enterprise architecture, security, and governance for regulated industries
- Experience mentoring engineers and presenting to executive stakeholders

Preferred

- Hands-on experience with Neo4j (or an equivalent graph database) and knowledge graph/ontology design for enterprise semantic layers
- Production deployment experience across multiple major cloud platforms (AWS, Azure, and GCP) - spanning AI/ML services, managed databases, and serverless compute
- Experience integrating real-time conversational voice or avatar interfaces into enterprise applications
- Familiarity with no-code/low-code AI platforms (e.g., Microsoft Power Platform, Copilot Studio, or equivalent) and how they fit into an enterprise agentic AI strategy
- Relevant cloud architecture or graph-database certifications

Education

- Bachelor's/Master's in Computer Science, Engineering, or related field

Locations

- Job No. ATCI-5748831-S2074204 | Hyderabad | Required Skill: Data Science

📌 Data Science Practitioner (India)
🏢 Accenture
📍 India