Agentic Solutions-AI and Data Science Engineer III

Deloitte Consulting seeks an AI and Data Science Engineer III for its Agentic Solutions work in Bengaluru, Hyderabad, Pune or Chennai. The role focuses on architecting, building and deploying enterprise-scale generative AI and agent-based solutions, alongside software pipelines and data and AI platforms. It involves working with clients and global, cross-functional teams throughout the project lifecycle.

Responsibilities

• Lead discussions with business and functional analysts to clarify requirements, assess integration impacts and prepare technical architecture and designs. Develop solutions to established integration and quality standards; create development guides, templates and scripts that automate routine tasks.
• Lead delivery from estimation and planning through execution, deployment and metric tracking. Facilitate daily scrum meetings, manage deliverables, review work, report weekly to leadership and mentor junior team members.
• Architect and improve AI models and agentic systems; deliver large-scale AI and generative AI projects across industries. Work with data engineers, ML/AI engineers, prompt engineers, onsite clients and other stakeholders from project inception to implementation. Participate in pre-sales, client pursuits and proposals.
• Contribute to the team's work modernizing data and analytics platforms, integrating structured and unstructured data, and applying automation and AI to generate insights and improve clients' data ecosystems.

Required qualifications

• 6-9 years of relevant hands-on experience in generative AI, deep learning or NLP; a BE, B.Tech, MCA, MSc or equivalent degree from an accredited university.
• Hands-on Python and SQL; LLM implementation and fine-tuning for custom and domain-specific applications; agentic AI architectures, Model Context Protocol, tool calling and multi-agent systems.
• Expertise in LangChain and LlamaIndex; experience with Azure AI Foundry, LLMOps, CI/CD, REST and FastAPI development, microservices, RAG implementation and optimization, and transformer architecture. Knowledge of Azure, AWS and GCP offerings and current agentic and generative AI research is required.

Preferred qualifications

Knowledge of Neo4j or other graph databases; Docker, Kubernetes and orchestration tools; production AI monitoring and observability tools. An AI or cloud certification from a premier institute is preferred.