AI Engineer Consultant
Deloitte
Kansas City, MO (In Person)
$132,150 Salary, Full-Time
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Job Description
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 /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.
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 /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.
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 All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with To view full details and how to apply, please login or create a Job Seeker accountSimilar remote jobs
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