AI Data Engineer - Consultant
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(Codex)/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.
- 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(Codex)/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.
- 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.
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