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 10/30/2026.

Work you'll do

As an AI Engineer III on the HC Forward team, you will be responsible for designing, building, and running the trusted, governed data, feature, and retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

• Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
• Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
• Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
• Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
• Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
• Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry), and contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.

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 workstreams
• 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

The team

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.

Qualifications

Required:

• Bachelor’s degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
• 4 years building and delivering large language model (LLM) and generative artificial intelligence (GenAI) solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration
• 4 years implementing retrieval-augmented generation (RAG)/retrieval, including document processing, embeddings, vector/hybrid search, and enterprise governance controls
• 4 years of modern data and AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, feature engineering/serving fundamentals, and production real-time inference services, including application programming interface (API) design, latency/performance, and reliability patterns
• 4 years leading platform/integration engineering across enterprise systems, including API/integration experience with Representational State Transfer (REST), GraphQL, event-driven architecture, microservices, and middleware
• 4 years of Development and Operations (DevOps) or Development, Security, and Operations (DevSecOps) experience, including CI/CD, infrastructure as code (IaC) such as Terraform/CloudFormation, Docker/Kubernetes, and observability/monitoring
• 4 years leading security/compliance efforts, including experience with enterprise security controls such as identity and access management (IAM), encryption, secrets, and audit logging; and data/privacy controls such as PII, retention, and access controls
• Ability to travel 0–25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.

Preferred:

• Master of Science (MS) or Doctor of Philosophy (PhD) degree and/or cloud and AI/ML certifications
• 4 years of experience with Human Capital platforms and integrations, including Workday, SAP SuccessFactors, Oracle HCM, or Salesforce, and HR data domains
• 4 years of experience operationalizing LLMOps/MLOps capabilities, including evaluation, monitoring, governance workflows, and model/prompt/version management; and 4 years of cloud experience on one or more of Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), including managed data platforms and scalable compute patterns
• 4 years of experience using structured problem solving to translate business needs into requirements, acceptance criteria, and shippable increments; and 4 years of experience explaining AI/GenAI trade-offs involving quality, latency, cost, and risk to stakeholders and documenting decisions
• 4 years of experience collaborating across product, data science/ML, data engineering, platform, and security; and 4 years of experience performing threat testing, monitoring, and operational-readiness activities
• 4 years of experience identifying consent, PII, and bias boundaries and escalating appropriately; experience supporting SOC 2, General Data Protection Regulation (GDPR), or Health Insurance Portability and Accountability Act (HIPAA) requirements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $122,000 to $240,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#HCFY27

Salary : $122,000 - $240,500