Description :

Role Summary :

The Chief Solutions Architect (AI Solutions) will lead the end-to-end technology vision, architecture, and delivery strategy for AI-driven Environmental, Health & Safety (EHS) solutions.

This role focuses on designing intelligent computer vision systems, enabling scalable AI/ML workflows, ensuring enterprise-grade product readiness, and supporting testing and solution validation for production environments.

The position provides strategic architectural leadership while driving technical excellence, innovation, and compliance alignment across AI-powered EHS platforms.

Key Responsibilities (KRA) :

Technology Leadership & Strategy :

- Define, own, and execute the technology roadmap for AI-led EHS compliance solutions.

- Architect scalable, secure, cloud-ready platforms for computer vision, ML pipelines, and data-driven insights.

- Ensure system performance, cybersecurity posture, and enterprise-grade reliability.

AI Architecture & Solution Design :

- Lead design of end-to-end AI/ML workflows, including model development, edge deployment, backend services, and dashboards.

- Architect robust API frameworks and integration layers for IoT, ERP, HRMS, command centers, and third-party systems.

- Evaluate, adopt, and operationalize emerging AI technologies, tools, and accelerators.

Support & Testing Deliverables :

- Oversee functional and technical validation of AI models, EHS modules, and integrated system components.

- Ensure structured test planning, scenario design, model validation, and quality assurance of deployments.

- Collaborate with engineering teams to troubleshoot production issues, address performance gaps, and refine model accuracy.

- Guide auto-testing strategies, benchmarking, and continuous monitoring of solution behavior.

Engineering & Technical Leadership :

- Mentor teams on architecture best practices, code standards, model deployment, and DevSecOps guidelines.

- Review system design, sprint deliverables, and technical documentation to ensure architectural coherence.

- Resolve critical technical issues, scalability challenges, and operational bottlenecks.

Stakeholder, Client & Regulatory Engagement :

- Represent the technology function during client discussions, PoCs, demos, and architecture workshops.

- Translate regulatory, compliance, and business requirements into scalable technical designs.

- Engage with safety experts, auditors, and domain specialists to align solutions with evolving EHS norms.

Innovation & Continuous Improvement :

- Drive differentiation through advanced automation, predictive analytics, and intelligent alerting systems.

- Build a data-driven culture improving model precision, system stability, and user experience.

- Contribute to long-term product evolution and innovation strategy.

Required Skillsets :

- Strong expertise in AI/ML, computer vision, and data engineering architectures.

- Proven experience designing scalable cloud-native platforms (AWS/Azure/GCP).

- Hands-on knowledge of model pipelines, MLOps, edge computing, and microservices.

- Proficiency in API design, integrations, and enterprise system interoperability.

- Experience with testing frameworks, validation workflows, and AI model benchmarking.

- Strong understanding of DevSecOps, CI/CD, and secure deployment principles.

- Ability to diagnose complex technical issues across AI systems, backend platforms, and cloud infrastructure.

- Excellent communication, stakeholder management, and client-facing presentation skills.

Behavioral Competencies :

- Strong ownership mindset and ability to navigate ambiguity.

- Strategic thinking with high attention to detail.

- Collaborative leadership with mentoring capability.

- Innovation-driven and outcome-focused