Senior PIM & AI Solutions Engineer

Job description

Overview: Johnson Controls is seeking a highly skilled Senior PIM & AI Solutions Engineer to accelerate our enterprise product data platform with next‑generation AI capabilities. This role blends deep PIM engineering expertise with hands‑on AI solution development, leveraging Inriver Inspire AI, large language models (LLMs), AI agents, content generation/translation engines, and productivity automation frameworks. You will partner with product owners, architects, and Product Marketing to deliver intelligent, scalable solutions that improve product content quality, streamline enrichment workflows, automate data transformations, and enhance speed‑to‑market. This includes enabling Inspire AI features, building validation workflows, generating data‑loader templates from intake sheets, and evaluating new AI tools that drive operational efficiency across the product content lifecycle. Responsibilities Build (PIM, AI, and Workflow Engineering) Enable, configure, and optimize Inriver Inspire AI features for content generation, localization, translation, and enrichment. Design and implement AI agent–driven workflows for content validation, attribute completeness checks, enrichment task routing, automated suggestions, and metadata generation. Build automations for intake‑to‑PIM transformations, including generating data loader sheets, mapping templates, cleansing rules, and exception handling. Design and evolve product data models (entities, attributes, CVLs, relationships), taxonomy/classification structures, validation rules, and versioning strategies. Engineer bulk data onboarding processes including imports, ETL transformations, AI‑assisted cleanup, and quality checks. Integrate PIM with AI services/agents, translation services, downstream systems, and internal applications via REST APIs, message/event‑based patterns, and workflow orchestration. Produce technical documentation including AI workflow designs, prompt & tool catalogs for agents, integration specs, data models, and operational runbooks. AI Enablement & Productivity Innovation Evaluate, prototype, and operationalize AI/ML tools and agent frameworks to improve productivity across Product Marketing and product content operations. Build internal AI utilities/agents for tasks such as content rewriting, translation, categorization, attribute derivation, and taxonomy recommendations. Establish best practices for prompt engineering, tool calling, retrievers, model selection, evaluation metrics (quality, latency, cost), and human‑in‑the‑loop (HITL) review. Ensure ethical, secure, and compliant use of AI within enterprise guidelines (governance, data privacy, PII/PI policy adherence). Platform & Engineering Excellence Apply OOP/SOLID principles and modern engineering practices to deliver maintainable and scalable PIM/AI solutions. Implement unit/integration tests and participate in CI/CD processes (Azure DevOps pipelines or equivalent). Drive data governance standards including completeness, consistency, accuracy, localization, lineage, and auditability. Promote best practices for agent safety/guardrails, evaluation harnesses, and continuous improvement in an Agile/Scrum environment. Required Qualifications Bachelor’s degree in computer science, Engineering, or related field, or equivalent experience. 6–8 years of engineering experience with C#/.NET, REST APIs, and MS SQL Server. 2+ years of hands‑on experience building AI-driven applications, including LLM workflows, RAG pipelines, prompt orchestration, or automated content-generation systems. Practical experience developing or integrating AI agents using frameworks such as Azure AI Orchestration, Semantic Kernel, Lang Chain, or equivalent tool‑calling architectures. Experience with Azure OpenAI or comparable LLM platforms (model configuration, prompt design, evaluation, cost optimization). Strong understanding of enterprise AI patterns: retrieval-augmented generation (RAG), embeddings, translation/normalization pipelines, content quality evaluation, and human‑in‑the‑loop (HITL) review loops. Hands‑on experience implementing automated workflows, data transformations, and bulk import processes. Knowledge of PIM concepts, including data modeling, enrichment workflows, validation, localization, and taxonomy. Strong debugging and optimization skills for both PIM workflows and AI-driven automations. Excellent communication skills and ability to work across engineering, Product Marketing, and data governance teams. Preferred Qualifications Inriver PIM experience (strongly preferred): advanced configuration of entities/links/CVLs, Inspire AI tuning, workflow customization, extensibility, connectors, and operational monitoring. Experience designing enterprise-grade AI solutions beyond basic prompting, such as multi-agent coordination, planning capabilities, or workflow orchestration frameworks. Hands-on experience with RAG optimization (embeddings tuning, vector index design, evaluation frameworks) and enterprise search technologies. Familiarity with AI quality evaluation, A/B testing, prompt safety guardrails, observability, and monitoring for model performance or agent behavior. Experience implementing AI-driven translations or localization pipelines at scale (e.g., Azure Translator, Language Studio, or 3rd‑party translation engines). Understanding of ML Ops / AI Ops concepts, including model lifecycle management, logging, cost governance, and versioning. Experience building automation solutions for product content operations (intake-to-PIM flows, automated validation gates, bulk enrichment, or classification systems). Knowledge of event-based integration patterns, pub/sub architectures, and microservices. Exposure to data governance, stewardship processes, and omnichannel content syndication.