AI/Synthetic Engineer

Summary Build the organization’s synthetic-audience capability: the data-grounding layer that connects first-party audience data to large language models, the synthetic-audience models themselves, and the engineering pipelines and evaluation harness around them. Direct the synthetic-capability partner and the foundation-model infrastructure beneath it and operate the validation harness that the team will use to judge accuracy. This is an engineering role at heart but applied entirely to research questions. Responsibilities Design and build the first-party data grounding layer (embeddings / retrieval) that anchors synthetic audiences in real segment data. Build, tune, and maintain synthetic-audience models and the prompt/evaluation pipelines around them. Operate the validation harness: run synthetic output against real holdout data and surface accuracy bounds for the Verification & Validation Data Scientist to interpret. Direct the synthetic-capability partner; manage foundation-model infrastructure and keep the architecture portable across providers. Build guardrails that prevent confident-but-wrong output from reaching stakeholders unflagged. Protect data ownership and ensure member data never trains external shared models. Education & Experience Requirements Education ·         Bachelor’s degree in computer science or related field or relevant equivalent experience in lieu of degree.  Master’s degree preferred. Experience Seven (7) or more years in ML/LLM engineering or applied data science, including production systems. Hands-on experience with LLM application development: grounding/RAG, prompt engineering, and evaluation frameworks. Exposure to synthetic data, agent-based simulation, or survey/behavioral data preferred. Experience directing an AI/ML vendor or platform partner preferred.   Certifications - NA Knowledge, Skills & Abilities Strong data engineering: pipelines, embeddings, working with first-party datasets. Understanding of model evaluation and the failure modes of generative systems. Able to work to research-defined validation standards rather than ship unchecked. Ability to effectively leverage artificial intelligence (AI) tools and technologies to streamline workflows, enhance productivity, and improve overall work quality.   Physical Requirements This position operates in a typical office environment (which includes a home office setting) and requires the ability to perform essential job functions with or without reasonable accommodation. Physical requirements may include: Prolonged periods of sitting at a desk and working on a computer. Frequent use of hands and fingers for typing, handling documents, and using office equipment. Occasional standing, walking, bending, and reaching. Ability to lift and carry up to 30 pounds as needed. Clear verbal and written communication skills for effective interaction with colleagues and stakeholders. Work Environment Hybrid Schedule (3 Days In-Office/2 Days Remote) This position follows a hybrid work schedule, with Tuesday through Thursday in office and Monday and Friday remote.  Employees must be available during standard business hours, with core hours beginning between 8:00–9:00 a.m. and concluding between 5:00–6:00 p.m. local time. Travel:  Occasional 0 – 10% #LI The hiring range for this position is $110,000 to $135,000 per year. This range is an estimate, and the actual salary may vary based on the candidate's experience, skills, and qualifications. SHRM offers a competitive and comprehensive total rewards package. The benefits for this position include professional growth and development, health, dental, vision, well-being, health savings, flexible spending, retirement, open leave, and annual discretionary bonus and incentives.