Job description

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-, Gemini-class, and other models, with strong governance, observability, and cost/performance discipline. Recruiting for this role ends on 10/30/2026. Work you'll do As an AI and Data Science Engineer II on the HC Forward team, you will be responsible for designing, building, and running the trusted, governed data, feature, and retrieval layer used by artificial intelligence/machine learning (AI/ML) and generative artificial intelligence (GenAI) solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for predictive machine learning (ML) and large language model (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, including application programming interfaces (APIs), services, pipelines, and containers/serverless solutions that meet availability, performance, and security expectations. • Build and operationalize LLM-enabled capabilities, including copilots, human resources (HR) knowledge assistants, summarization, and policy question-and-answer experiences, using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns. • Implement LLM application patterns, including retrieval-augmented generation (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, including online/offline consistency, caching, latency service-level objectives (SLOs), and backfills. • Operationalize data quality and lineage and enable secure consumption patterns for predictive ML and LLM-based experiences. 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) • 2+ 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; and 2+ years implementing retrieval-augmented generation (RAG)/retrieval, including document processing, embeddings, vector/hybrid search, and enterprise governance controls. • 2+ years of data and artificial intelligence engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals; and 2+ years building production, real-time inference services, including application programming interface (API) design, latency/performance, and reliability patterns. • 2+ years leading platform/integration engineering across enterprise systems, including API/integration experience with Representational State Transfer (REST), GraphQL, event-driven capabilities, microservices, and middleware; and 2+ years of development operations (DevOps) and development, security, and operations (DevSecOps) experience, including continuous integration/continuous delivery (CI/CD), infrastructure as code (IaC) using Terraform/CloudFormation, Docker/Kubernetes, observability, and monitoring. • 2+ years leading security/compliance efforts, including enterprise security controls—identity and access management (IAM), encryption, secrets, and audit logging—and data/privacy controls—personally identifiable information (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. • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. Preferred: • Master’s or doctoral degree and/or cloud and artificial intelligence/machine learning (AI/ML) certifications. • 2+ years of experience with Human Capital platforms and integrations, including Workday, SAP SuccessFactors, Oracle HCM, Salesforce, and human resources (HR) data domains. • 2+ years of experience operationalizing large language model operations (LLMOps) and machine learning operations (MLOps) capabilities, including evaluation, monitoring, governance workflows, and model/prompt/version management; and 2+ years of cloud experience with one or more of Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), including managed data platforms and compute patterns. • 2+ years translating business needs into documented requirements, acceptance criteria, and shippable increments using structured problem solving; and 2+ years documenting and communicating AI/GenAI trade-offs involving quality, latency, cost, and risk to stakeholders. • 2+ years collaborating across product, data science/machine learning, data engineering, platform, and security functions; and 2+ years performing threat testing, monitoring, and operational-readiness responsibilities. • 2+ years applying ethics and privacy practices to recognize consent, personally identifiable information (PII), and bias boundaries and escalate concerns; and experience with System and Organization Controls (SOC) 2, the General Data Protection Regulation (GDPR), or the Health Insurance Portability and Accountability Act (HIPAA). 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 $91,100 to $179,500. 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

Requirements

Must-haves

Recruiting for this role ends on 10/30/2026.
Work you'll do
Implement LLM application patterns, including retrieval-augmented generation (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, including online/offline consistency, caching, latency service-level objectives (SLOs), and backfills.
Operationalize data quality and lineage and enable secure consumption patterns for predictive ML and LLM-based experiences.
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
Bachelor’s degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
Ability to travel 0–25%, on average, based on the work you do and the clients and industries/sectors you serve.
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
2+ years of experience with Human Capital platforms and integrations, including Workday, SAP SuccessFactors, Oracle HCM, Salesforce, and human resources (HR) data domains.
2+ years collaborating across product, data science/machine learning, data engineering, platform, and security functions; and 2+ years performing threat testing, monitoring, and operational-readiness responsibilities.

Nice-to-haves

Master’s or doctoral degree and/or cloud and artificial intelligence/machine learning (AI/ML) certifications.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlllmmachine learningapirestgraphqlci/cddockerkubernetesawsazuregcp

Platform: avature
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance