AI Engineer III

Deloitte is hiring an AI Engineer III for the HC Forward team to design, build, and run governed data, feature, and retrieval layers that support Human Capital AI products and GenAI solutions. The role focuses on delivering production-grade pipelines and services for model training, real-time inference, and LLM application workloads with governance, observability, and cost-performance discipline.

Location

Tampa, FL (onsite)

Compensation

• USD 122,000 - 240,500 per year
• The wage range estimate for this role is $122,000 to $240,500

Minimum Qualifications

• Bachelor’s degree in a STEM field
• 4+ years building and delivering large language model (LLM) and generative AI (GenAI) solutions using Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration
• 4+ years implementing retrieval-augmented generation (RAG)/retrieval, including document processing, embeddings, vector/hybrid search, and enterprise governance controls
• 4+ years modern data and AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, feature engineering/serving, and production real-time inference services (including API design, latency/performance, and reliability patterns)
• 4+ years leading platform or integration engineering across enterprise systems, including REST, GraphQL, event-driven architecture, microservices, and middleware
• 4+ years DevOps or DevSecOps experience, including CI/CD, infrastructure as code such as Terraform/CloudFormation, Docker/Kubernetes, and observability/monitoring
• 4+ years leading security and compliance efforts, including IAM, encryption, secrets, audit logging, and data/privacy controls such as PII, retention, and access controls
• Ability to travel 0-25%, on average
• Limited immigration sponsorship may be available

Role Responsibilities

• Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable designs and delivered solutions (APIs, services, pipelines, containers/serverless) aligned to availability, performance, and security expectations
• Build and operationalize LLM-enabled capabilities (examples include copilots, HR knowledge assistants, summarization, and 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 and chunking, embeddings, vector and 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 (PII handling, prompt-injection defenses, content filtering, policy-based access) in coordination with security and risk stakeholders
• Establish data and model reliability along with cost-performance discipline, covering data quality, schema evolution, lineage/metadata, monitoring, right-sizing, query tuning, and LLM token and 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

Technologies

Claude, GPT (Codex), Gemini, RAG, embeddings, vector search, hybrid search, APIs, LLM, GenAI, REST, GraphQL, event-driven architecture, microservices, middleware, CI/CD, Terraform, CloudFormation, Docker, Kubernetes, IAM, encryption, secrets, audit logging, PII, MLOps, LLMOps

Benefits

• Discretionary annual incentive program (subject to program rules, where an award, if any, depends on factors including individual and organizational performance)

HC Forward 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.

Preferred Qualifications

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

Travel

Ability to travel 0-25%, on average, based on the work performed and client/industry needs.