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Deloitte

Audits companies and advises on tax and technology

AI Engineer III

AI Application Engineering +1Posted on Nov 12
Full-timeAtlanta, GA, USA

About the Job

Requirements

  • A bachelor's degree in a STEM field, such as Computer Science, Engineering, Statistics, or Data Science.
  • At least 4 years building and delivering large language model and generative artificial intelligence solutions with Claude-, GPT/Codex-, or Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • At least 4 years implementing retrieval-augmented generation and retrieval, including document processing, embeddings, vector/hybrid search, and enterprise governance controls.
  • At least 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 API design, latency/performance, and reliability patterns.
  • At least 4 years leading platform/integration engineering across enterprise systems, including API/integration experience with REST, GraphQL, event-driven architecture, microservices, and middleware.
  • At least 4 years of DevOps or DevSecOps experience, including CI/CD, infrastructure as code such as Terraform/CloudFormation, Docker/Kubernetes, and observability/monitoring.
  • At least 4 years leading security/compliance efforts, including enterprise security controls such as 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 assigned work and clients and industries/sectors served.
  • Limited immigration sponsorship may be available.

Responsibilities

  • Design, build, and operate the trusted, governed data, feature, and retrieval layer used by AI/ML and GenAI solutions.
  • 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 APIs, services, pipelines, containers/serverless, meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities such as copilots, HR knowledge assistants, summarization, and policy Q&A using Claude/GPT(Codex)/Gemini-class models, 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, including online/offline consistency, caching, latency SLOs, and backfills.
  • Implement safety, privacy, and access controls, including PII handling, prompt-injection defenses, content filtering, and policy-based access, in collaboration with security and risk stakeholders.
  • Establish data/model reliability and cost-performance discipline through data quality, schema evolution, lineage/metadata, monitoring, right-sizing, query tuning, and LLM token/cost telemetry.
  • Contribute to MLOps/LLMOps and production operations, including versioning, reproducibility, CI/CD, automated testing, observability, and incident response; support design reviews, deployment readiness, and runbooks.

Desired Qualifications

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

About the Company

Deloitte

Audits companies and advises on tax and technology

Deloitte audits companies and advises businesses and governments on tax, technology, and risk, and it is one of the Big Four, the world's four largest accounting firms. In 1849 its founder became the first independent auditor of a public company, Britain's Great Western Railway. Its auditors check companies' financial reports for errors and fraud before investors rely on them, while its consultants design strategy, install business software, and defend clients against cyberattacks. Clients pay fees for each audit or project, and each country's Deloitte firm is a separate business owned by its local partners. Deloitte was founded in London in 1845 and is based in New York.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$17.1M
Headquarters
New York, NY
Founded
1845

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