Note: The job is a remote job and is open to candidates in USA. WAI Global is a leading aftermarket company headquartered in South Florida, focused on enhancing operational capabilities through AI and automation. The Director, AI Platform and Development Engineering will oversee the development of WAI's AI-ready data foundation and production AI platform capabilities, collaborating with various teams to deliver efficient and scalable AI solutions.
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
- Undertakes additional responsibilities and tasks as directed by management
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 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
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