AI Data Engineer – Senior Consultant

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Company Overview
A global professional services organization is seeking an AI Data Engineer – Senior Consultant to accelerate the development of AI and Human Capital solutions. The team partners with clients to build secure, scalable, and governed AI/ML products, including LLM and GenAI applications. The organization emphasizes innovation, analytics, and technology-driven transformation to improve business outcomes and HR experiences across industries.

Position Summary
The AI Data Engineer – Senior Consultant will design, build, and operate the data, feature, and GenAI foundations that power Human Capital AI products. This hands-on role involves delivering production pipelines, real-time inference services, and LLM-enabled applications while maintaining governance, observability, and cost/performance discipline. You will work closely with AI Data Engineers, AI Solutions Architects, and cross-functional teams including product, data science, security, and platform engineering.

Key Responsibilities

• Translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless)
• Build and operationalize LLM-enabled capabilities such as copilots, HR knowledge assistants, summarization, and policy Q&A using Claude, GPT/Codex, and Gemini-class models
• 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
• Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access)
• Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring, query tuning, 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

Required Qualifications

• Bachelor’s degree in STEM (Computer Science, Engineering, Statistics, Data Science)
• 4+ years delivering LLM/GenAI solutions (Claude/GPT/Codex/Gemini-class models)
• 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance
• 4+ years modern data & AI engineering (data modeling, batch/streaming pipelines, structured/unstructured processing, feature engineering/serving)
• 4+ years building production real-time inference services (API design, latency/performance, reliability patterns)
• 4+ years leading platform/integration engineering across enterprise systems (REST, GraphQL, event-driven, microservices, middleware)
• 4+ years DevOps/DevSecOps (CI/CD, IaC, Docker/Kubernetes, observability/monitoring)
• 4+ years leading security/compliance efforts (IAM, encryption, audit logging, SOC 2/GDPR/HIPAA exposure)
• Ability to travel 0–25% depending on client/project needs
• Limited immigration sponsorship may be available

Preferred Qualifications

• Advanced degree (MS/PhD) or relevant cloud/AI certifications
• Experience with Human Capital platforms and HR data domains (Workday, SAP SuccessFactors, Oracle HCM, Salesforce)
• Operationalizing LLMOps/MLOps (evaluation, monitoring, governance, model/prompt/version management)
• Cloud experience on AWS/Azure/GCP with managed data platforms and scalable compute
• Strong structured problem solving and stakeholder communication skills
• Ethics and privacy awareness, including consent, PII, and bias considerations

Disclaimer
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