AI and Data Science Engineer III

AI and Data Science Engineer III Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands‑on and delivery-oriented: you will ship production pipelines and services that support model training, real‑time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

As an AI and Data Science Engineer on the HC Forward team, you will be responsible for building and operating the governed data, feature, and retrieval foundations that support artificial intelligence, machine learning, and generative artificial intelligence solutions.

• Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product requirements into technical designs and delivered solutions, including application programming interfaces, services, pipelines, and containerized or serverless components
• Build and operationalize large language model-enabled capabilities, including copilots, knowledge assistants, summarization, and policy question‑and‑answer solutions using secure endpoints, tool calling, and reusable prompt and context patterns
• Implement retrieval‑augmented generation patterns, including document ingestion, chunking, embeddings, vector or hybrid search, and retrieval and evaluation telemetry
• Deliver governed datasets and feature engineering and serving patterns for machine learning training and real‑time inference, including online and offline consistency, caching, latency targets, and backfills
• Implement privacy, access, quality, lineage, monitoring, observability, testing, deployment, and incident response practices for production artificial intelligence and data solutions

A successful candidate would possess these skills:

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or work streams
• Ability to manage and prioritize multiple tasks in a fast‑paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to provide clear guidance to others

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market‑aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Required:

• Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or another STEM field
• 4+ years of experience building and delivering large language model or generative artificial intelligence solutions using Claude-, GPT-, or Gemini‑class models, including prompt design, context design, tool calling, evaluation, and production integration
• 4+ years of experience implementing retrieval‑augmented generation, document processing, embeddings, and vector or hybrid search in enterprise environments
• 4+ years of experience in data engineering, including data modeling, batch or streaming pipelines, structured and unstructured data processing, and feature engineering
• 4+ years of experience building production inference services and enterprise integrations using application programming interfaces, Representational State Transfer (REST), GraphQL, event‑driven patterns, continuous integration and continuous deployment, infrastructure as code, Docker, Kubernetes, and…