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Deloitte

Audits companies and advises on tax and technology

AI Engineer II

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

About the Job

Requirements

  • 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, such as Computer Science, Engineering, Statistics, or Data Science.
  • At least 2 years building and delivering large language model and generative artificial intelligence solutions using Claude-, GPT/Codex-, or Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration; and at least 2 years implementing retrieval-augmented generation or retrieval, including document processing, embeddings, vector/hybrid search, and enterprise governance controls.
  • At least 2 years of data and artificial intelligence engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals; and at least 2 years building production, real-time inference services, including application programming interface design, latency/performance, and reliability patterns.
  • At least 2 years leading platform/integration engineering across enterprise systems, including application programming interface/integration experience with Representational State Transfer, GraphQL, event-driven capabilities, microservices, and middleware; and at least 2 years of development operations and development, security, and operations experience, including continuous integration/continuous delivery, infrastructure as code using Terraform or CloudFormation, Docker/Kubernetes, observability, and monitoring.
  • At least 2 years leading security/compliance efforts, including enterprise security controls—identity and access management, encryption, secrets, and audit logging—and data/privacy controls—personally identifiable information, retention, and access controls.
  • Ability to travel 0–25% on average, based on the work performed and the clients and industries/sectors served.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Responsibilities

  • Design, build, and run the trusted, governed data, feature, and retrieval layer used by artificial intelligence/machine learning and generative artificial intelligence 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 application programming interfaces, services, pipelines, and container/serverless solutions that meet availability, performance, and security expectations.
  • Build and operationalize large language model-enabled capabilities, including copilots, human resources knowledge assistants, summarization, and policy question-and-answer experiences using Claude, GPT/Codex, or Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement large language model application patterns, including retrieval-augmented generation, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for machine learning training and real-time inference, including online/offline consistency, caching, latency service-level objectives, and backfills.
  • Operationalize data quality and lineage and enable secure consumption patterns for predictive machine learning and large language model-based experiences.

Desired Qualifications

  • Master’s or doctoral degree and/or cloud and artificial intelligence/machine learning certifications.
  • At least 2 years of experience with Human Capital platforms and integrations, including Workday, SAP SuccessFactors, Oracle HCM, Salesforce, and human resources data domains.
  • At least 2 years of experience operationalizing large language model operations and machine learning operations capabilities, including evaluation, monitoring, governance workflows, and model/prompt/version management; and at least 2 years of cloud experience with one or more of Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including managed data platforms and compute patterns.
  • At least 2 years translating business needs into documented requirements, acceptance criteria, and shippable increments using structured problem solving; and at least 2 years documenting and communicating artificial intelligence/generative artificial intelligence trade-offs involving quality, latency, cost, and risk to stakeholders.
  • At least 2 years collaborating across product, data science/machine learning, data engineering, platform, and security functions; and at least 2 years performing threat testing, monitoring, and operational-readiness responsibilities.
  • At least 2 years applying ethics and privacy practices to recognize consent, personally identifiable information, and bias boundaries and escalate concerns; and experience with System and Organization Controls 2, the General Data Protection Regulation, or the Health Insurance Portability and Accountability Act.

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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