D&T Machine Learning Engineer II

Overview

Lead the enablement, integration and scaling of agentic AI platforms within General Mills' Digital and Technology India team, building custom connectors, APIs and agent orchestration workflows.

What you'll do

• Lead the technical enablement, integration, and continuous enhancement of advanced agentic AI platforms, ensuring they adhere to stringent performance, scalability, reliability, and security standards, including evaluating new agentic-first platforms, tools and frameworks.
• Architect, design, develop, and implement robust custom connectors and integration solutions to seamlessly connect diverse data sources, enterprise applications, and external services with agentic platforms.
• 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.
• Develop, implement, and optimize sophisticated strategies for orchestrating complex agent workflows, managing inter-agent communication, and enhancing decision-making processes within the platform.
• Collaborate with other engineering teams to establish, implement and support comprehensive monitoring and observability capabilities for agentic workflows.
• Conduct ongoing optimization, performance tuning, and lifecycle management of agentic platforms, including bug fixes, security patches, and capacity planning.
• 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.
• Create and maintain comprehensive, high-quality technical documentation for platform architecture, custom connectors, API specifications, operational procedures, and best practices.
• Ensure all platform development and integrations adhere to enterprise security policies, data privacy regulations, and compliance standards.
• Continually invest in your own knowledge and skillset through formal training, reading, and attending conferences and meetups.

What you'll need

• Bachelor's or master's degree in computer science, Software Engineering, Artificial Intelligence, Data Science, or a closely related technical field.
• 5-7 years of progressive experience in software engineering, platform development, or a related technical field, with a strong focus on building scalable and resilient systems.
• Minimum of 1-2 years of hands-on, in-depth experience specifically with Generative AI (Gen AI) and Agentic AI technologies, platforms, and frameworks (e.g., LangChain, LlamaIndex, AutoGen, Glean, etc.).
• Proven track record of designing, developing, and deploying complex integrations and custom connectors for enterprise-level applications.
• Expert-level proficiency in at least one modern programming language (e.g., Python, Java, Go) with a strong emphasis on writing clean, efficient, and maintainable code.
• Deep understanding and extensive experience with API design principles, development, and rigorous testing (RESTful APIs, GraphQL, gRPC).
• Demonstrated expertise in building custom connectors and integrating diverse systems, including enterprise applications (e.g., Salesforce, SAP, ServiceNow) and various data sources.
• Good understanding/working experience of agent orchestration frameworks, multi-agent systems, and techniques for managing complex agent interactions and decision flows.
• Extensive experience with major cloud platforms (Google Cloud Platform is preferred) and their AI/ML services (Vertex AI is preferred).
• Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance.
• Working knowledge of MCP connections, RAG, Vectors, Embeddings and Indexing, Knowledge graph and OAuth flows.
• Exceptional problem-solving and analytical capabilities, with a keen eye for detail and a proactive approach to identifying and resolving complex technical challenges.
• Superior communication and collaboration skills, with the ability to articulate technical concepts clearly to both technical and non-technical stakeholders.
• Ability to thrive in a fast-paced, dynamic environment, working both independently and as a key contributor within cross-functional teams.
• Passion for learning new technologies and solving challenging problems.

Nice to have

• Background in building, maintaining, and supporting traditional ML pipelines in a GCP environment.
• Understanding of the Consumer-Packaged Goods (CPG) industry.
• Familiarity with AI/ML lifecycle stages and MLOps concepts.
• Strong understanding and practical experience with MLOps principles and practices, including CI/CD for AI/ML workflows, model versioning, and deployment strategies.
• Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms.
• Familiarity with Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation).
• Ability to collaborate with cross-functional teams and provide tech mentorship to other stakeholders.
• Strong leadership potential with the ability to mentor junior engineers and drive best practices.

Details

• Location: Powai, Mumbai, Maharashtra, India.
• Applicants must meet minimum age qualifications in the country in which the job is located.