Sr. D&T Machine Learning Engineer (Agentic Ai)

General Mills; Mumbai; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

General Mills, Digital and Technology India, is seeking a Sr. ML Engineer (Agentic Engineer) to join the D&T AI and Automation (AIA) Organization. You will lead the development of agentic AI platforms powering data-driven decision making at scale.

The role focuses on architecture, integration, and optimization of agentic workflows, including monitoring, security, and governance, with exposure to cloud platforms like GCP and AWS.

Qualifications

• Experience leading agentic AI platform initiatives and integration.
• Strong API design and data integration capabilities.
• Familiarity with cloud platforms (GCP/AWS) and distributed systems.
• Knowledge of telemetry, observability, and ROI metrics for agentic solutions.

Responsibilities

• Enable and enhance agentic AI platforms with robust design, performance, and security.
• Develop custom connectors to link diverse data sources and applications.
• Design, test, and secure APIs for internal/external systems supporting agentic workflows.
• Architect, orchestrate, and optimize multi-agent workflows for reliable decision making.
• Establish monitoring, observability, and reliability practices across platforms.

Skills

Agentic AI

API design

Custom connectors

Cloud: GCP/AWS

LLM Ops

Monitoring

Security & Compliance

Technical leadership

Tools

APIs

Job description

COMPANY OVERVIEW

We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best - bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what's next.

OVERVIEW

General Mills, Digital and Technology India, is seeking a Sr. ML Engineer (Agentic Engineer) to join the D&T AI and Automation (AIA) Organization. The Sr. ML Engineer (Agentic Engineer) will be a key technical leader within the Digital & Technology organization, focused on building the next generation of Agentic AI and ML platforms that power data-driven decision making at scale.

This team builds enterprise-level scalable and sustainable AI solution pipelines and Agentic workflows to serve the AI and Agentic needs of business-impacting problem statements, maintains cloud and agentic platforms, and explores new complementary tooling for AI and Intelligent automation requirements.

KEY ACCOUNTABILITIES

• Advanced Agentic Platform Enablement: Lead the technical enablement, integration, and continuous enhancement of advanced agentic AI platforms, workflow design, agentic architecture ensuring they adhere to stringent performance, scalability, reliability, and security standards. This includes evaluating new agentic-first platforms, tools and frameworks.
• Custom Connector & Integration Development: Architect, design, develop, and implement robust custom connectors and integration solutions to seamlessly connect diverse data sources, enterprise applications, and external services with our agentic platforms.
• API Design, Testing & Integration: Drive the design, development, and rigorous testing of APIs, ensuring secure, reliable, and efficient integration with both internal and external systems to support agentic workflows.
• Agent Orchestration & Workflow Management: Develop, implement, and optimize sophisticated strategies for orchestrating complex agent workflows, managing inter-agent communication, and enhancing decision‑making processes within the platform to achieve desired business outcomes.
• Monitoring, Observability & Reliability Engineering: Strong understanding and working knowledge to collaborate with other engineering teams to establish, implement and support comprehensive monitoring and observability capabilities for Agentic workflows across multiple platforms.
• Knowledge of LLM Ops (Agent quality, telemetry, and FinOps) Working knowledge of end-to-end telemetry for agents (tracing, feedback loops, success metrics, cost and latency dashboards), for driving continuous evaluation of agent quality, safety, and ROI (e.g., task success, deflection, CSAT, cycle‑time). Use these insights to tune prompts, tools, and workflows.
• ML Systems Engineering: Research, operationalize, and standardize ML tooling and processes, including installation, maintenance, documentation, and best practices.
• Generative & Agentic AI Architecture Knowhow: Comprehensive knowledge and working experience (preferred) of setting up an Agentic ecosystem with a hyperscaler like Google Cloud Platform (GCP) or Amazon Web Services(AWS).
• Platform Optimization & Lifecycle Management: Conduct ongoing optimization, performance tuning, and lifecycle management of agentic platforms and their underlying capabilities, including bug fixes, security patches, and capacity planning.
• Drive Agile Agentic POCs: Strong working knowledge and experience to develop & lead solution prototypes from ideation, scoping, implementation, and future road mapping with internal and vendor led teams. Drive agile POC execution with focus on hands‑on capability validation on new emerging tools and platforms.
• Expert‑Level Troubleshooting & Support: Provide advanced technical support and expert-level troubleshooting for complex issues related to agentic platform functionality, integrations, and performance, performing root cause analysis and implementing preventative measures.
• Technical Documentation Excellence: Create and maintain comprehensive, high‑quality technical documentation for platform architecture, custom connectors, API specifications, operational procedures to ensure knowledge transfer and system maintainability.
• Governance & Best Practices: Help develop, collaborate, and establish Governance best practices, enterprise standards for Agentic tooling & new agentic solutions.
• Security & Compliance: Ensure all platform development and integrations adhere to enterprise security policies, data privacy regulations, and compliance standards.
• Embrace learning mindset: Continually invest in your own knowledge and skillset through formal training, r