AI Engineer Senior Consultant
Deloitte · Detroit, MI
- On site
- Full-time
- $150,000 / year
- Detroit, MI
Job highlights
- Build and operate AI/GenAI foundations for Human Capital.
- Design, build, and run trusted, governed data layers.
- Develop LLM-enabled capabilities with Claude/GPT/Gemini.
- Implement RAG, embeddings, and vector search patterns.
- Ensure reliable, secure, and scalable AI solutions.
About the role
About the Role
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 and a Lead AI Solutions Architect, 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.
Work You'll Do
As an AI Engineer Senior 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 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).
- Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and 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)
- 4+ 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.
- 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
- 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
- 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
- 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
- 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
- 4+ 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.
- Limited immigration sponsorship may be available
Preferred Qualifications
- Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
- 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
- 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
- 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
- 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
- 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
- 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
- 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
- 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.
Key skills/competency
- AI Engineering
- GenAI Solutions
- LLM Operations (LLMOps)
- Data Engineering
- Machine Learning (ML)
- Cloud Platforms (AWS/Azure/GCP)
- DevOps/DevSecOps
- API Design & Integration
- Security & Compliance
- Production Deployment
Skills & topics
- AI Engineer
- Senior Consultant
- GenAI
- LLM
- Machine Learning
- Data Engineering
- Cloud Computing
- DevOps
- Consulting
- Human Capital
How to get hired
- Tailor your resume: Highlight your 4+ years of experience with LLM/GenAI solutions, RAG implementation, data engineering, and DevOps. Quantify achievements where possible.
- Showcase technical skills: Emphasize expertise in Claude/GPT/Gemini, cloud platforms (AWS/Azure/GCP), and CI/CD practices.
- Demonstrate problem-solving: Prepare examples of translating business needs into technical designs and delivering production-ready AI services.
- Understand the team: Research Deloitte's Human Capital innovation and HC Forward's mission to modernize HR.
- Prepare for interviews: Be ready to discuss your experience with security, privacy, and AI ethics in production environments.
Technical preparation
Master LLM frameworks (Claude, GPT, Gemini).,Build and deploy RAG and vector search systems.,Practice modern data engineering pipelines.,Solidify CI/CD and infrastructure as code (IaC).
Behavioral questions
Describe a complex AI solution you delivered.,How do you ensure AI model reliability?,How do you handle data privacy in AI?,Explain AI trade-offs to non-technical stakeholders.
Frequently asked questions
- What are the key technologies used by the AI Engineer Senior Consultant at Deloitte?
- The AI Engineer Senior Consultant role at Deloitte focuses on building and operating AI and GenAI foundations. Key technologies include LLM models like Claude, GPT/Codex, and Gemini, along with RAG (Retrieval-Augmented Generation) patterns, embeddings, vector search, and modern data engineering tools for batch/streaming pipelines and feature serving. Experience with cloud platforms (AWS, Azure, GCP) and DevOps/DevSecOps practices is also crucial.
- What is the expected level of experience for the AI Engineer Senior Consultant position at Deloitte?
- Deloitte requires a minimum of 4+ years of experience for the AI Engineer Senior Consultant role. This experience should specifically cover building and delivering LLM/GenAI solutions, implementing RAG/retrieval mechanisms, modern data & AI engineering, developing real-time inference services, platform/integration engineering, and DevOps/DevSecOps.
- What is Deloitte's approach to security and compliance for AI solutions?
- Deloitte emphasizes trusted, governed data and secure AI solutions. The AI Engineer Senior Consultant is responsible for implementing safety, privacy, and access controls, including PII handling, prompt-injection defenses, content filtering, and policy-based access. Familiarity with enterprise security controls and data/privacy regulations like SOC 2, GDPR, and HIPAA is valued.
- How does Deloitte foster innovation within its Human Capital team?
- Deloitte's Human Capital team, specifically the HC Forward initiative, acts as a dedicated innovation partner. They accelerate the future of Human Capital by building market-aligned products, platforms, and services that leverage AI, data, and engineering to modernize HR experiences and outcomes, indicating a strong focus on cutting-edge technologies and solutions.
- What are the opportunities for career growth as an AI Engineer Senior Consultant at Deloitte?
- As a Senior Consultant at Deloitte, you'll be working on cutting-edge AI and GenAI solutions with a focus on client impact and innovation. The role involves close collaboration with various teams, exposure to diverse projects, and the opportunity to deepen expertise in LLMOps, MLOps, and cloud technologies, which are critical for career advancement in the AI field.
- Can I apply for the AI Engineer Senior Consultant role at Deloitte if I don't have a STEM degree?
- Deloitte requires a Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science) for the AI Engineer Senior Consultant position. While an advanced degree is preferred, a foundational STEM degree is listed under the required qualifications.