Senior Manager - Agentic AI Platform

Ecolab Food Safety & Hygiene Solutions Private Limited; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Ecolab Food Safety & Hygiene Solutions Private Limited seeks a Senior Manager - Agentic AI Platform to lead strategy, governance, security, and operations for enterprise AI platforms. You will shape roadmap, establish governance, and ensure reliable, compliant AI across the organization.

You'll collaborate with Enterprise Architecture, Data & AI, Security, and Platform Engineering teams to enable scalable AI Agents, build orchestration frameworks, and drive cost-efficient, secure deployments in

Qualifications

• Bachelor's or master's degree in computer science, Engineering, Data Science, or related field.
• 10+ years of experience in software engineering, AI/ML platforms, cloud platforms, or enterprise platform management.
• 5+ years of leadership experience managing engineering or platform teams.

Responsibilities

• Define and execute the vision, roadmap, and operating model for the enterprise Agentic AI Platform.
• Lead platform engineering teams responsible for AI infrastructure, tooling, and operational support.
• Drive platform adoption across business domains and enterprise AI initiatives.
• Design and manage the enterprise orchestration layer for AI agents.
• Define enterprise AI security architecture and controls.

Education

Bachelor's or master's degree in computer science, Engineering, Data Science, or related field

Tools

Kubernetes

Docker

Databricks

Azure AI Foundry

Snowflake

Job description

Position Summary

The Senior Manager - Agentic AI Platform will lead the strategy, architecture, governance, security, and operational management of the enterprise Agentic AI Platform. This role is responsible for building and managing the foundational platform capabilities required to scale AI Agents across the enterprise, including agent orchestration frameworks, LLM platform services, AI security controls, governance frameworks, observability, and operational excellence. The individual will work closely with Enterprise Architecture, Data & AI teams, Security, Platform Engineering, and Business stakeholders to establish a secure, scalable, and governed Agentic AI ecosystem that accelerates AI adoption while ensuring compliance, reliability, and responsible AI practices.

Key Responsibilities

Agentic AI Platform Leadership

Define and execute the vision, roadmap, and operating model for the enterprise Agentic AI Platform. Establish platform capabilities that enable the development, deployment, and management of AI Agents at scale. Lead platform engineering teams responsible for Agentic AI infrastructure, tooling, and operational support. Drive platform adoption across business domains and enterprise AI initiatives.

Orchestrator Layer & Multi-Agent Framework Design

Design and manage the enterprise orchestration layer for AI agents. Establish standards for agent-to-agent communication, workflow orchestration, task planning, memory management, and tool integration. Build reusable frameworks that accelerate agent development and deployment. Enable integration with enterprise systems, APIs, data sources, and workflow platforms.

LLM Platform Management

Own enterprise LLM services and model infrastructure. Evaluate, onboard, and manage proprietary and open-source foundation models. Establish model lifecycle management processes, including model selection, benchmarking, deployment, monitoring, and optimization. Drive LLM cost management, performance optimization, and reliability engineering.

AI Governance & Responsible AI

Define and implement AI governance frameworks, policies, and operating procedures. Establish controls for Responsible AI, model risk management, auditability, explainability, and regulatory compliance. Partner with Legal, Risk, Compliance, and Information Security teams to ensure AI solutions meet enterprise requirements. Create governance reporting and executive dashboards for AI platform adoption and risk management.

AI Security & Compliance

Define enterprise AI security architecture and controls. Implement safeguards against prompt injection, jailbreak attacks, data leakage, model abuse, and unauthorized access. Establish identity, access management, and secret management controls for AI services. Ensure compliance with organizational security standards, privacy regulations, and industry best practices.

Observability & Platform Operations

Establish comprehensive monitoring for agent performance, model behaviour, platform reliability, and operational health. Define SLAs, SLOs, and platform support processes. Build automated incident management and operational response capabilities. Drive continuous improvement through platform telemetry and analytics.

Stakeholder & Team Leadership

Lead a team of AI Platform Engineers, MLOps Engineers, AI Security Specialists, and Platform Administrators. Collaborate with Enterprise Architects, Data Engineering, Security, and Business stakeholders. Provide technical leadership, mentoring, and talent development. Manage vendor relationships and strategic technology partnerships.

Qualifications

• Bachelor's or master's degree in computer science, Engineering, Data Science, or related field.


• 10+ years of experience in software engineering, AI/ML platforms, cloud platforms, or enterprise platform management.


• 5+ years of leadership experience managing engineering or platform teams.


• Experience building and operating enterprise AI/ML platforms.


• Hands-on experience with LLMs, Generative AI, Agentic AI frameworks, and cloud-native architectures.

Preferred Technical Skills

• Agentic AI Frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents, etc.)


• LLM Platforms (Azure OpenAI, OpenAI, Anthropic, Gemini, Open-Source Models)


• MLOps and AI Operations


• Kubernetes, Docker, API Gateways Databricks, Azure AI Foundry, Snowflake Security by Design and Zero Trust Architecture AI Governance and Responsible AI Frameworks DevSecOps and Platform Engineering Practices

Success Metrics

• Enterprise adoption of Agentic AI Platform.


• Reduction in time to deploy production-grade AI agents.


• AI platform reliability, scalability, and operational efficiency.


• Compliance with AI governance and security standards.


• Successful implementation of Responsible AI controls.


• Optimized LLM usage, performance, and cost management.


• Improvement in developer productivity and AI solution delivery velocity.

Leadership Profile

A strategic technology leader who combines platform engineering expertise, AI innovation, governance discipline, and operational excellence to build a secure, scalable, and enterprise-grade Agentic AI ecosystem.

Experience Level Senior Level