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AI Engineer Consultant

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 August 30, 2026
Work You'll Do:

As an AI Engineer Consultant, you will design, build, and run the trusted, governed data + feature + 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.
Key Responsibilities:
* Partner with the Lead AI Solutions Architect and AI Data Engineer to design, build, and deploy secure, scalable AI solutions (APIs, services, pipelines, containers/serverless) that meet availability, performance, and security requirements.
* Build and operationalize LLM-enabled products (copilots, HR knowledge assistant, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including prompt/context patterns and tool/function calling.
* Implement RAG and document intelligence patterns (ingestion, chunking, embeddings, vector/hybrid search) plus evaluation and retrieval telemetry.
* Deliver governed data and features for ML/GenAI (curated datasets, feature pipelines/serving) supporting training and real-time inference, including consistency, caching, backfills, and latency SLOs.
* Implement trust, safety, and governance controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk partners.
* Drive engineering excellence and operations (CI/CD, testing, versioning/reproducibility, monitoring/observability, incident response) and cost/performance optimization (right-sizing, query tuning, token/cost telemetry).
* Support design/deployment readiness through reviews, decision documentation, and operational runbooks.
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.
Required Qualifications:
* Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
* 2+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
* 2+ years with RAG/retrieval (embeddings, vector/hybrid search, document processing) and enterprise governance controls.
* 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
* 2+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
* 2+ years leading platform/integration engineering to improve interoperability, reliability, and time-to-market across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
* 2+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
* 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
* Ability to travel 0-25%, on average, based on client and project needs.
* 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 Qualifications:
* Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
* 2+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
* 2+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
* 2+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
* 2 + years of experience with structured problem solving: translating business needs into requirements, acceptance criteria, and shippable increments.
* 2+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
* 2+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
* 2+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
* 2 + years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

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 $93,000 to $171,300.

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.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Minneapolis, Morristown, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY26 #IIOFY26

AI Engineer Consultant

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 August 30, 2026
Work You'll Do:

As an AI Engineer Consultant, you will design, build, and run the trusted, governed data + feature + 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.
Key Responsibilities:
* Partner with the Lead AI Solutions Architect and AI Data Engineer to design, build, and deploy secure, scalable AI solutions (APIs, services, pipelines, containers/serverless) that meet availability, performance, and security requirements.
* Build and operationalize LLM-enabled products (copilots, HR knowledge assistant, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including prompt/context patterns and tool/function calling.
* Implement RAG and document intelligence patterns (ingestion, chunking, embeddings, vector/hybrid search) plus evaluation and retrieval telemetry.
* Deliver governed data and features for ML/GenAI (curated datasets, feature pipelines/serving) supporting training and real-time inference, including consistency, caching, backfills, and latency SLOs.
* Implement trust, safety, and governance controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk partners.
* Drive engineering excellence and operations (CI/CD, testing, versioning/reproducibility, monitoring/observability, incident response) and cost/performance optimization (right-sizing, query tuning, token/cost telemetry).
* Support design/deployment readiness through reviews, decision documentation, and operational runbooks.
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.
Required Qualifications:
* Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
* 2+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
* 2+ years with RAG/retrieval (embeddings, vector/hybrid search, document processing) and enterprise governance controls.
* 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
* 2+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
* 2+ years leading platform/integration engineering to improve interoperability, reliability, and time-to-market across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
* 2+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
* 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
* Ability to travel 0-25%, on average, based on client and project needs.
* 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 Qualifications:
* Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
* 2+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
* 2+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
* 2+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
* 2 + years of experience with structured problem solving: translating business needs into requirements, acceptance criteria, and shippable increments.
* 2+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
* 2+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
* 2+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
* 2 + years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

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 $93,000 to $171,300.

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.

Possible Locations: Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Minneapolis, Morristown, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, S...