JOB SUMMARY:
Radwell International is the parent/holding company for many individual branded companies. The companies can be thought of today within 4 Business Units: Radwell, Radwell International, Group CBS, and Electrical Source. The four BUs work in the distribution of electrical and automation parts (including new, surplus, obsolete and refurbished), service and repair of factory automation equipment and electrical controls and circuitry. Each of the 4 BUs have P&L accountability and drive to growth agendas that are coordinated yet independent.
RESPONSIBILITIES
Radwell is in the middle of a transformation to become a tech-enabled, AI-driven global digital distributor by modernizing eCommerce, ERP, CRM, pricing, contact center, and data platforms while scaling capabilities globally. AI is central to this transformation from dynamic pricing, demand forecasting, recommendations, and search relevance to intelligent email mining, CX analytics, and automation across operations.
The Director of AI, Enterprise Architecture, DevOps & Quality Engineering is a key leadership role responsible for building and scaling the AI-first technology foundation that powers Radwell’s digital business.
• 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.
This is a hands-on leadership role at the intersection of AI, architecture, DevOps, SRE, and QA, with a global team footprint.
AI-First Architecture Leadership (Enterprise, Application, Data & Integration)
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).
• Data/feature pipelines, online/offline feature stores, and real-time streaming for AI.
• Secure and governed integration of AI services into transactional systems.
• 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.
DevOps, Platform Engineering & AIOps
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.
• Secure, compliant, and repeatable environments for development, testing, staging, and production.
• Design and implement an AIOps strategy that uses AI/ML to operate Radwell’s digital ecosystem:
o Intelligent monitoring for web, ERP, CRM, AI services, and integrations.
o Anomaly detection, proactive incident prevention, and noise-reduced alerting.
o Automated root-cause analysis and self-healing workflows for critical paths (search, pricing, checkout, order processing, CX).
o 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.
AIOps, MLOps & AI Platform Enablement
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.
Ensure AI platforms are secure, observable, cost-optimized, and compliant with Radwell’s policies and relevant regulations.
Quality Engineering for AI & Digital Platforms
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).
• Seamless integration of automated tests in CI/CD pipelines.
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.
People Leadership & Global Collaboration
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.
• Work closely with ISSC leadership to make the Bengaluru center a core hub for DevOps, MLOps, QE, and AIOps at Radwell.
Governance, Security, Compliance & Vendor Ecosystem
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.
Ensure vendors and partners operate in line with Radwell’s architecture, cost, and reliability objectives.
Minimum Qualifications
**KNOWLEDGE & SKILLS REQUIRED **
EDUCATION & EXPERIENCE
Benefits: Radwell offers a comprehensive benefits package including health, dental, and vision coverage. The Company provides company sponsored short-term and long-term disability benefits, as well as $50,000 in Life insurance. These benefits, along with additional voluntary benefits, are available to all regular full-time employees beginning on first day of employment. All employees are automatically enrolled at 3% into the Company’s 401(k) Plan on the first of the month following 90 days of continuous employment. Employees are eligible for common paid Company Holidays and 15 days of PTO annually, which begin accruing on first date of employment and may be used immediately upon joining the team.
Salary Information: The recruiting base salary range for this full time position is $180,000 - $225,000/year. Within the range, individual pay is determined by factors, including job-related skills, experience, and relevant education or training. Additionally, this role is bonus-eligible, with a target bonus percentage that provides an opportunity to earn even more based on company performance.
Required Skills
Required Experience