Job Title: Senior AI/ML Engineer — Customer Data Platform and Identity Resolution
Location: Frisco, TX / Atlanta, GA – Onsite
In-person interview at client end.
CDP MISSION: Our mission is to be the authoritative source of truth for customer data — delivering timely, high-quality data at scale to power the contextual experiences that drive the growth of this company. Every customer profile must be accurate, trusted, and available when it matters, across every touchpoint, for the entire US adult population.
Job Overview
We are seeking a Senior AI/ML Engineer to lead the design and development of the advanced AI systems that make our Customer Data Platform (CDP) the authoritative source of truth for customer data — covering the entire US adult population.
This role owns the intelligence layer of CDP: production-grade identity resolution at massive scale, and LLM-powered interfaces that make trusted customer data accessible to every stakeholder in the organization. You will architect systems that resolve billions of customer records into accurate, unified profiles — and build the natural language interfaces that let business users query and understand that data without writing SQL.
You will drive architecture decisions, define best practices, and lead the development of systems where accuracy, trust, and timeliness are non-negotiable.
Job Responsibilities — Identity Resolution
- Design and lead end-to-end identity resolution architecture, combining probabilistic models, ML, and embedding-based techniques to build the authoritative customer identity graph
- Build and optimize large-scale entity matching systems across billions of records and multiple data domains — ensuring every US adult is accurately represented in CDP
- Architect advanced candidate generation and blocking strategies (LSH, phonetic encoding, semantic similarity) that balance precision with computational feasibility at population scale
- Design high-precision matching pipelines using ensemble approaches (rules + ML + LLM-based validation) to maximize accuracy of golden customer profiles
- Develop scalable clustering and graph-based approaches for unified customer identity resolution with clear confidence scoring and auditability
- Lead implementation of embedding pipelines and similarity search systems using transformer models for semantic-level identity matching
Job Responsibilities — AI/LLM
- Architect and build LLM-powered systems for entity resolution, including zero-shot and few-shot classification workflows that handle edge cases traditional models miss
- Design and implement RAG-based architectures for enriching and contextualizing customer data from unstructured sources
- Lead development of NLQ-to-SQL platforms, enabling business users to query CDP — the authoritative source of truth — using natural language
- Translate ambiguous business questions into structured queries with schema awareness, semantic layers, and guardrails that protect data integrity
- Define best practices for prompt engineering, evaluation, and LLM observability — ensuring AI outputs meet the trust standards CDP demands
- Design and optimize vector search architectures (Pinecone, Qdrant, pgvector) for large-scale retrieval across customer data
- Evaluate and integrate emerging frameworks such as LangChain, LangGraph, and agentic workflows where they strengthen CDP capabilities
Education and Work Experience
- Bachelor's or Master's degree in Computer Science, Data Science, or related field
- 6+ years of experience in ML/AI engineering
- Proven experience building production-grade entity resolution or identity graph systems at scale
- Experience designing LLM-based applications in enterprise environments with high accuracy and trust requirements
Technical Skills
- Advanced programming: Python
- Deep expertise in ML algorithms for similarity, classification, and clustering — particularly in identity resolution contexts
- Strong experience with transformer models, embeddings, and semantic search at population scale
- Hands-on experience with LLM APIs and orchestration frameworks
- Strong SQL and experience with distributed data processing (Spark, Dask)
- Experience with vector databases and ANN search systems (FAISS, Pinecone, etc.)
- Expertise in ML lifecycle management (MLflow or equivalent)
- Understanding of data governance, privacy, and security requirements for customer identity data
Knowledge, Skills, and Abilities
- Strong system design and architectural thinking for AI/ML systems at population scale
- Ability to balance precision, recall, and scalability in identity resolution systems — understanding that accuracy directly impacts CDP's authority as the source of truth
- Strong understanding of data semantics and customer domain modeling across diverse data sources
- Leadership in driving AI engineering best practices, standards, and quality benchmarks
- Ability to collaborate across data engineering, product, security, and business teams to deliver trusted customer intelligence
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