Senior Consultant - GenAI Full Stack Developer

GenAI Full Stack Developer - Senior Consultant

Deloitte's Audit & Assurance professionals help organizations navigate business risks and opportunities-across financial, operational, information technology (IT), business, and regulatory areas-to build resilience and accelerate performance. In this role, you'll design and deliver end-to-end Generative AI (GenAI) solutions - including Retrieval-Augmented Generation (RAG) and agentic AI - that are production-ready, scalable, and aligned to enterprise risk and governance expectations.

• Lead business and technical requirements elicitation with client stakeholders; own end-to-end gap analysis; translate needs into solution architecture, detailed technical specifications, and delivery-ready backlog artifacts.
• Drive design, build, test, and deployment of full-stack Generative AI (GenAI) applications (web user interface (UI), backend services, and data/model components); ensure non-functional requirements (security, performance, reliability) are met.
• Own end-to-end retrieval-augmented generation (RAG) implementations (ingestion, chunking, embedding, indexing, retrieval, orchestration); define prompt engineering standards and evaluation harnesses to measure quality and reduce hallucinations.
• Architect agentic AI workflows (tool-using agents, multi-step orchestration, multi-agent patterns); integrate into enterprise platforms and business processes with appropriate controls, auditability, and human-in-the-loop checkpoints.
• Lead model training, fine-tuning, and validation; establish evaluation approaches and key performance indicators (KPIs) for quality, robustness, bias/safety, and cost/latency; run benchmarking and iteration cycles to meet acceptance criteria.
• Own API and integration service design; deliver scalable RESTful interfaces; coordinate integration with downstream/upstream systems, identity and access management (IAM), and operational workflows.
• Lead extract, transform, load (ETL) and data engineering pipeline delivery to curate governed datasets for GenAI solutions; partner with data governance and risk teams on lineage, access controls, and data quality standards.
• Operationalize deployments using containerized patterns and cloud services; implement monitoring/observability (performance, cost, drift, quality signals) and drive continuous improvement through incident learnings and release management.
• Advise on emerging GenAI models, frameworks, and toolkits; prototype and recommend options with explicit tradeoffs across value, delivery effort, risk, compliance, and total cost of ownership (TCO).
• Collaborate with cross-functional teams (product, engineering, data, risk, and stakeholders) to deliver adoption-ready solutions and documentation.

Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape.

Learn more about Deloitte Audit & Assurance.

• Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field (advanced degree a plus).
• 4+ years of experience in software engineering, full stack development, and/or AI/ML solution delivery.
• Python programming (production-grade) and strong SQL.
• Natural Language Processing (NLP) applied to GenAI solutions.
• Agentic AI design/implementation, including Lang Chain, Lang Graph, and Llama Index.
• Hands-on experience with RAG architectures and implementation.
• Strong prompt engineering (design, iteration, and evaluation).
• Experience with vector databases (e.g., Pinecone, Chroma, FAISS or similar) and embedding-based retrieval.
• Experience with GenAI model build: training, fine-tuning, and validation; practical LLM evaluation using common metrics.
• Experience with model deployment (serving, monitoring, iteration) and production hardening.
• Experience with containers (e.g., Docker) and scalable runtime patterns.
• Experience building ETL pipelines and data engineering solutions (data quality, preprocessing, and curation).
• API development and integration (RESTful services); backend development using FastAPI (or equivalent).
• Full stack web development with JavaScript/Type Script.
• Proficiency with HTML/CSS and preprocessors (SASS/LESS).
• Experience with front-end frameworks (React, Angular, or Vue).
• Working knowledge of UI/UX design principles (accessibility, usability, responsive design).
• Experience with cloud AI/ML services across Azure, AWS, and GCP, including Vertex AI.
• You should reside within a commutable…