AI Engineer, Commercial

Church & Dwight is building AI-powered capabilities to help Commercial teams make better decisions and operate more effectively, and the Commercial Agentic Pod is at the center of that effort. As an AI Engineer, Commercial, you will design, build, deploy, and scale reliable generative AI products with a focus on large language models, retrieval-augmented generation (RAG), and agentic workflows.

This hybrid role is based in Ewing, NJ, with in-person attendance required on Tuesdays, Wednesdays, and Thursdays and remote work options on Mondays and Fridays. The salary range for this position is USD 71,000 - 101,100 per year.

What you will do

• Translate Commercial business needs into secure, scalable AI products that combine approved enterprise knowledge, structured and unstructured data, models, tools, permissions, and human oversight.
• Design, build, test, deploy, and maintain LLM and generative AI applications, including agentic workflows and orchestration patterns (planning, routing, tool use, memory, handoffs, and human-in-the-loop controls).
• Build and optimize RAG systems using vector databases and embeddings, covering chunking, indexing, metadata, hybrid search, reranking, grounding, and source attribution, along with traceable ingestion and refresh processes.
• Engineer reusable production prompts and integrations for generative AI APIs, enterprise services, applications, analytical models, workflow tools, and knowledge repositories.
• Create automated and human evaluation processes for accuracy, groundedness, safety, relevance, task completion, latency, cost, and usability, and monitor quality, adoption, incidents, and business outcomes.
• Identify risks including hallucination, prompt injection, tool issues, retrieval failures, and operational risks, then implement guardrails and controls such as fallbacks, authentication, authorization, logging, secrets management, and data controls.
• Apply strong software engineering practices, including modular design, source control, code review, automated testing, documentation, release management, and production support.
• Collaborate with Commercial stakeholders and partners across Data Science, GTA, architecture, data engineering, platform, security, privacy, and governance from discovery and prototyping through deployment, training, adoption, and continuous improvement.
• Ensure alignment with enterprise architecture and requirements for privacy, security, legal compliance, data governance, and responsible AI, including documenting architecture, controls, dependencies, procedures, limitations, and intended use.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Engineering, Information Systems, or a related technical discipline required.
• 3+ years of experience in software engineering, machine learning engineering, AI engineering, data engineering, or a related discipline required.
• Hands-on experience building LLM and generative AI applications, including production prompt engineering, structured outputs, tool calling, model selection, APIs, evaluation, testing, monitoring, and optimization.
• Experience building enterprise RAG solutions with vector databases, embeddings, retrieval pipelines, knowledge sources, hybrid retrieval, reranking, grounding, and source attribution.
• Experience with agent frameworks and workflow orchestration, including routing, handoffs, memory patterns, and human-in-the-loop controls.
• Proficiency in Python, REST APIs and SDKs, cloud AI services, source control, automated testing, authentication, and authorization.

Technologies

• Python
• REST APIs, SDKs
• Cloud AI services
• Vector databases, embeddings, chunking, indexing
• Hybrid search, reranking, grounding
• Authentication, authorization, logging, secrets management
• Source control, automated testing, observability

Benefits

• Medical, dental, vision
• Basic life insurance
• Paid vacation and sick time
• Paid Parental Leave
• Paid holidays, floating holidays, and vacation days starting in their first year of employment depending on hire date
• 401k retirement plan with company match and profit-sharing
• Discounted Employee Stock Purchase Plan