Role & responsibilities

1. AI & Agentic Platform Leadership

- Own and drive the architectural transition of the EHS platform toward agentic AI, including the design and deployment of autonomous AI agents capable of executing multi-step EHS compliance, incident investigation, and risk assessment workflows.

- Define the strategy for integrating large language models (LLMs) and generative AI into EHS workflows, including AI-assisted report generation, regulatory interpretation, audit support, and natural language querying.

- Establish AI model governance frameworks covering data privacy, bias mitigation, model explainability, auditability, and compliance with emerging AI regulations (e.g., EU AI Act).

- Drive adoption of MLOps practices to ensure reliable, scalable, and continuously improving AI model deployment across the EHS product suite.

- Evaluate and select AI frameworks, agentic orchestration platforms (e.g., LangChain, AutoGen, CrewAI or equivalent), and LLM providers appropriate for enterprise EHS use cases.

- Ensure all AI capabilities are developed with end-user trust, transparency, and regulatory defensibility as first principles.

- Own the platform's AI regulatory compliance programme ensuring AI agents deployed in the EHS platform meet applicable governance, safety, and risk management requirements across different target markets (EU, UK, US, China and others), including technical documentation, human oversight mechanisms, and conformity assessment readiness.

1. R&D; Organisation Leadership

- Lead, inspire, and develop a globally distributed R&D; organisation, with primary engineering centres in South Korea and India.

- Build and maintain a high-performance engineering culture founded on psychological safety, continuous improvement, and technical excellence.

- Define and implement scalable R&D; operating models that accommodate time zone complexity, cultural diversity, and asynchronous collaboration.

- Own talent acquisition, workforce planning, performance management, and succession planning across the global R&D; function.

- Mentor and develop senior engineering leaders, fostering a pipeline of internal talent for key technical and managerial roles.

- Champion diversity, equity, and inclusion within the R&D; organisation.

1. Product & Technical Strategy

- Collaborate with Product Management to co-author the multi-year EHS product roadmap, ensuring R&D; capacity and capability are aligned to strategic priorities.

- Provide technical oversight and architectural governance across all EHS platform modules incident management, risk assessment, permit-to-work, environmental monitoring, regulatory compliance, training management, and AI-powered analytics.





- Champion the evolution from on-premise and hybrid deployments toward a cloud-native, SaaS-first EHS platform architecture.

- Oversee the design of open APIs, data interoperability standards, and ecosystem integration capabilities to support customer enterprise environments.

- Maintain technology radar and guide the adoption of emerging technologies relevant to EHS software.

1. Global Collaboration & Communication

- Serve as a senior technical ambassador, representing R&D; in interactions with customers, prospects, partners, regulators, and industry forums.

- Present AI strategy, product roadmap, and technical vision to C-suite stakeholders, customer executive teams, and at industry conferences.

- Facilitate effective cross-functional collaboration between R&D;, Product Management, Sales, Customer Success, and Executive Leadership.

- Establish clear communication rhythms, escalation paths, and decision-making frameworks across geographically distributed teams.

1. Quality, Compliance & Risk Management

- Ensure the EHS R&D; function operates within quality management frameworks consistent with ISO 9001 and ISO 27001 standards.

- Maintain rigorous software development lifecycle (SDLC) governance, including security-by-design, data protection, and regulatory compliance across target markets.

- Oversee risk identification and mitigation processes within the R&D; organisation, including technical debt management, platform resilience, and business continuity planning.

- Ensure AI systems deployed within the EHS platform meet applicable regulatory, ethical, and industry standards in all operating jurisdictions.

Preferred candidate profile

- Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a closely related technical discipline/experience. (Required)

- PhD in a relevant field Computer Science, AI/ML, Environmental Engineering, or Industrial Safety is advantageous.

- Relevant professional certifications in AI, cloud architecture (e.g., AWS Solutions Architect, Google Cloud Skilled), or EHS management (e.g., NEBOSH, ISO 14001 Lead Auditor) are a plus.

Professional Experience

- Minimum 15 years of progressive experience in enterprise software product development,



with a strong track record of delivering commercially successful products at scale.

- Minimum 7 years in senior R&D; leadership roles (e.g., VP Engineering, R&D; Director, Head of Engineering) within a global software organisation.

- Demonstrated experience leading R&D; teams across multiple geographies and time zones, with specific experience working with teams in APAC and/or South Asia.

- Proven track record of successfully leading AI/ML product initiatives from concept through production deployment in enterprise environments.

- Direct experience with agentic AI frameworks, LLM integration, and the operationalisation of generative AI in enterprise SaaS products. (Strongly preferred)

- Experience in EHS, HSE, environmental compliance, industrial safety, or related regulatory domains is highly desirable.

- Demonstrable experience managing R&D; organisations of 30+ engineers across multiple teams and functions.

Technical Expertise

- Deep expertise in AI/ML technologies: large language models, agentic AI orchestration, retrieval-augmented generation (RAG), machine learning pipelines, and MLOps.

- Strong fluency in modern cloud-native architectures: microservices, containerisation (Kubernetes, Docker), serverless computing, and multi-cloud platforms (AWS, Azure, GCP).

- Solid experience with SaaS product architecture, multi-tenancy, API design, and platform scalability.

- Familiarity with AI governance frameworks, responsible AI principles, and emerging regulatory requirements (e.g., EU AI Act, NIST AI RMF).

- Proficiency with modern SDLC practices: Agile/SAFe, DevSecOps, CI/CD, test automation, and code quality management.

- Knowledge of data architecture, analytics platforms, and business intelligence tooling relevant to EHS reporting and regulatory compliance.

- Experience with enterprise integration standards, open APIs, and interoperability within complex customer IT environments.

Leadership & People Management

- 10+ years of direct people management experience, including management of senior technical leaders and engineers.

- Proven ability to build, scale, and sustain high-performing, diverse, and geographically distributed engineering organisations.

- Strong servant-leadership mindset: ability to inspire, coach, and develop technical talent at all levels.

- Experience navigating organisational change, including technology platform transitions and the cultural shift to AI-first product development.

- Demonstrated success in cross-functional collaboration with Product, Commercial, Customer Success, and Executive teams.

- Experience managing third-party development partners, system integrators, and technology vendors.

📌 Global HEAD OF EHS Research & Development (Kolkata)
🏢 LabVantage Solutions
📍 Kolkata