Note: The job is a remote job and is open to candidates in USA. WAI is a global aftermarket leader headquartered in South Florida, focused on leveraging AI and data capabilities to improve operational efficiency. The Director, AI Platform and Development Engineering will lead the development of WAI's AI-ready data foundation and oversee the technical architecture for AI automation strategies.
Responsibilities
- Lead the design, build, deployment, and continuous improvement of WAI's AI-ready data and platform foundation across sales, inventory, planning, catalog, customer, order, product, and related business systems
- Design, build, and govern a centralized data lake that consolidates critical data from ERP and other core business systems into a single trusted foundation, enabling AI tools, models, and analytics to reliably access enterprise data
- Identify repetitive and manual tasks, use process mining to uncover workflow bottlenecks, and implement RPA solutions to improve efficiency and streamline operations
- Own technical architecture for AI/ML/LLM workflows, RAG, embeddings, vector search, structured data query, dashboards, APIs, model serving, and monitoring
- Connect, ingest, clean, validate, normalize, and automate data pipelines from structured and unstructured sources, including enterprise systems, reports, documents, PDFs, spreadsheets, and business notes
- Build or oversee a trusted unified data layer with schema standards, data-quality monitoring, lineage, source traceability, and failure detection
- Develop and support machine learning and statistical methods for revenue trends, sales forecasting, anomaly detection, stock monitoring, shortage/overstock prediction, demand forecasting, variance analysis, and risk identification
- Build grounded LLM workflows that connect to trusted WAI data, generate AI summaries, support natural-language business questions, reduce hallucinations, and return business-friendly explanations with source references
- Implement embeddings and vector search capabilities using pgvector or other approved vector database technologies, tuned for retrieval precision, speed, broad scanning, and deep analysis
- Build or support dashboards, KPIs, forecasts, anomaly alerts, AI summaries, drill-down to source data, automatic refresh, and exportable leadership or business reports
- Deploy reliable pipelines, models, APIs, dashboards, and LLM workflows while optimizing inference cost, latency, GPU memory, throughput, model selection, and production performance
- Implement role-based access control, auditability, data governance, source traceability, monitoring, evaluation, and verifiable AI outputs in partnership with IT/security stakeholders
- Provide technical direction to offshore AI engineers, data/integration engineers, vendors, and implementation partners
- Partner with the AI Automation Director and business-facing teams to ensure platform work is aligned to approved use cases, business value, adoption needs, and governance priorities
- Evaluate hosted AI services, open-source models, AI/ML frameworks, orchestration tools, and proof-of-concepts; recommend when to use hosted models versus self-hosted or WAI-tuned models
Skills
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Data Science, Machine Learning, Artificial Intelligence, or a related technical field required
- 10+ years of experience in software engineering, data engineering, AI/ML engineering, enterprise architecture, analytics engineering, cloud engineering, or related technical roles
- Experience designing or leading production data platforms, data lakes or lakehouses, analytics platforms, AI/ML platforms, LLM/RAG solutions, model workflows, APIs, or enterprise integration architectures
- Hands-on experience with data pipelines, SQL, Python, APIs, cloud platforms, data modeling, orchestration, monitoring, and production support practices
- Hands-on experience with LLMs, RAG, embeddings, vector databases, prompt/evaluation workflows, AI agents, model serving, and AI orchestration frameworks required
- Experience directly managing or providing technical direction to offshore/remote engineering teams required, as this role's direct reports will be based offshore
- Master's degree preferred; equivalent senior technical experience may be considered
- Experience with ERP, CRM, catalog, inventory, planning, customer, order, or product data in an operationally complex business preferred
- Experience directing contractors, vendors, or implementation partners also preferred
- Experience with cloud platforms such as Azure, AWS, or GCP; experience with model serving, GPUs, containerization, MLOps, observability, or cost optimization preferred
- Familiarity with LangChain, LangGraph, OpenAI APIs, Azure AI, Microsoft Copilot, open-source models such as Llama, Mistral, Qwen, or similar tools preferred
- Certifications in cloud platforms, data engineering, AI/ML, cybersecurity, enterprise architecture, Microsoft Azure AI, MLOps, or related technical areas are preferred
Company Overview