Radwell International · 1 day ago
Director - AI, Architecture, DevOps & QA
Willingboro, NJ
Full-time
Onsite
Director/Executive
$180K/yr - $225K/yr
7+ years expRadwell International is the parent company for various branded companies focused on the distribution of electrical and automation parts. The Director of AI, Architecture, DevOps & QA is responsible for leading the transformation to an AI-driven digital distributor, overseeing the integration of AI platforms with core systems, and managing global teams to enhance operational efficiency.
AutomotiveTelecommunicationsTransportation
Responsibilities
Own the AI platform architecture and its integration with core systems (eCommerce, ERP, CRM, WMS, contact center, pricing)
Lead DevOps, AIOps, and MLOps to industrialize how Radwell builds, deploys, and operates AI-enabled applications and services
Build a modern Quality Engineering function that ensures AI and non-AI workloads are reliable, safe, and performant in production
Partner with business and product leaders to translate Radwell’s AI and digital strategy into scalable, secure, and cost-efficient platforms
Define And Own Radwell’s AI-centric Target Architecture Across eCommerce and digital experience, ERP (e.g., Epicor P21, NetSuite), CRM (Salesforce), Contact center (Genesys), Pricing, inventory, and forecasting platforms, Enterprise data & AI platforms
Drive the evolution from point-to-point integrations to a composable, event-driven, API-first architecture that makes AI services reusable across channels and systems
Define reference architectures for AI/ML workloads (pricing optimization, demand forecasting, recommendations, lead scoring, email intelligence, anomaly detection)
Champion data quality, MDM, and data governance as prerequisites for reliable AI models
Collaborate with Product, Data, Security, and Business stakeholders to ensure architecture decisions are driven by customer experience, revenue growth, and operational efficiency
Build and lead a Platform Engineering & DevOps organization responsible for standardized CI/CD pipelines (e.g., GitHub Actions, Azure DevOps) for apps, APIs, and ML workloads
Infrastructure-as-Code for cloud resources (AWS/Azure), Kubernetes/ECS, databases, and data/AI infrastructure
Design and implement an AIOps strategy that uses AI/ML to operate Radwell’s digital ecosystem: Intelligent monitoring for web, ERP, CRM, AI services, and integrations
Anomaly detection, proactive incident prevention, and noise-reduced alerting
Automated root-cause analysis and self-healing workflows for critical paths (search, pricing, checkout, order processing, CX)
Capacity and performance forecasting for peak seasons and promotions
Partner with IT Operations and Security to build a unified observability stack (logs, metrics, traces, events) that feeds AIOps and SRE practices
Establish and operate MLOps foundations for all AI use cases at Radwell, including: Dynamic pricing and discount optimization, Inventory and demand forecasting, Recommendation and personalization engines, AI-driven email and opportunity detection, CX analytics and agent assist
Build And Own AI & ML Lifecycle And Governance: Model development, experimentation, and approval workflows, Automated model deployment via CI/CD, blue-green/canary strategies, Model registry, versioning, and rollback, Model and data drift monitoring, performance tracking, and scheduled retraining, Controls for bias, explainability (where needed), and safe rollout
Collaborate With Data Engineering And AI/ML Teams To Design feature stores and data contracts, Reusable AI services exposed via well-designed APIs to eCommerce, ERP, CRM, and contact center
Own the Quality Engineering strategy for Radwell’s application and AI landscape: eCommerce and digital properties, ERP, CRM, WMS, and integrations, AI APIs, models, and pipelines
Build a Test Automation-first Culture: Automated tests at unit, API, integration, UI, performance, and security levels, Specialized testing for AI components (data validation, model performance, regression vs. baseline, fairness checks where appropriate)
Define QE metrics and dashboards that connect to business outcomes: Defect escape rate, test coverage, and automation ratio, Release frequency and change failure rate, Uptime, response time, order accuracy, and CX SLAs
Scale QE capabilities in collaboration with the India Shared Services Center, ensuring efficient follow-the-sun regression and release validation
Build And Lead a Cross-functional, Global Team Spanning Solution & platform architects, DevOps & Platform engineers, SREs & AIOps engineers, MLOps engineers, QA/QE and test automation engineers
Mentor and develop technical leaders, establish clear role definitions and career paths, and promote continuous learning around AI, cloud, and automation
Create a culture of outcome-driven engineering: experiment, measure, learn, and iterate
Define Architecture And Platform Governance: Design reviews, standards, and guardrails, Management of technical debt and modernization priorities, Change management processes tailored to agile/DevOps and AI experimentation
Embed security and privacy into the AI platform, DevOps pipelines, and QA processes (DevSecOps, data masking, least-privilege access, audit trails)
Lead Evaluation And Management Of Tooling And Partners Across Cloud platforms (AWS/Azure), Observability and AIOps, MLOps platforms and AI services, Test automation and quality tools, Systems integrators and AI/ML vendors
Qualification
Required
7-10 years in Enterprise architecture/ Software engineering (5+ in leadership) delivering modern platforms on AWS/Azure roles spanning multiple domains such as Architecture, DevOps/Platform, SRE, MLOps, or QE
Proven experience designing and implementing cloud-native, scalable architectures (AWS and/or Azure) for high-traffic digital platforms (eCommerce, B2B portals, or similar)
Demonstrated, hands-on leadership in AI-enabled systems—either building AI platforms, integrating AI services into production systems, or running MLOps and AIOps in production
Strong background in DevOps & Platform Engineering: CI/CD, infrastructure-as-code, containers/orchestration, observability, and SRE practices
Experience building or maturing MLOps capabilities: model lifecycle, deployment, monitoring, retraining, and governance
Experience leading Quality Engineering for complex, integrated enterprise environments (ERP, CRM, WMS, integrations, web, mobile, and APIs)
Solid understanding of data engineering, data pipelines, and analytics/AI use cases, and how they tie into core business processes
Background in distribution, manufacturing, supply chain, or similarly operational businesses
Strong people leadership skills with experience managing global or offshore teams (ideally India) and driving change across multiple stakeholder groups
Excellent communication skills; able to explain AI/architecture decisions in business language to executives and non-technical stakeholders
Proven track record operationalizing AI/ML (RAG/LLMs, forecasting, recommendations) and MLOps (feature stores, CI/CD, observability, evaluation)
Executive communication and stakeholder management across corporate and BU leaders
Bachelor's degree in Computer Science, Engineering, or related field; master's degree a plus
Benefits
Health, dental, and vision coverage
Company sponsored short-term and long-term disability benefits
$50,000 in Life insurance
Additional voluntary benefits
401(k) Plan
Common paid Company Holidays
15 days of PTO annually
Company
Radwell International
Radwell, established in 1979, is a global leader in industrial automation solutions, providing new, never-used, refurbished, obsolete, and hard-to-find automation, industrial, electrical, and MRO components to businesses of all sizes.
1001-5000 employees
H1B Sponsorship
Radwell International has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (1)
Funding
Current Stage
Late StageTotal Funding
$200MKey Investors
Greenbriar Equity Group
2022-04-04Acquired
2021-01-01Private Equity· $200M
Leadership Team
Scott Vaughn
Chief Strategy Officer (CSO)
Recent News
Google Patent
2024-04-14
Google Patent
2024-04-14
2023-08-08
Company data provided by crunchbase