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Powai, Mumbai, MH
Live, first seen by us 1 day agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design and build custom connectors linking data sources and enterprise apps to agentic platforms
Design, develop and test APIs for secure integration with internal and external systems
Develop and optimize orchestration of complex agent workflows and inter-agent communication
Tune, patch and maintain agentic platforms, including capacity planning
Troubleshoot platform issues and perform root cause analysis
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.
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
Conduct ongoing optimization, performance tuning, and lifecycle management of agentic platforms and their underlying capabilities, 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
Deep understanding and extensive experience with API design principles, development, and rigorous testing (RESTful APIs, GraphQL, gRPC).
Ability to thrive in a fast-paced, dynamic environment, working both independently and as a key contributor within cross-functional teams.
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.
Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance.
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.
Experience & Education: - 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.
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Day 1
Early. Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
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Technical Skills: - 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).
- 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.
- 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) is a plus.
- 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.
PREFERRED QUALIFICATIONS - Background in building, maintaining, and supporting traditional ML pipelines in a GCP environment. - Understanding of the Consumer-Packaged Goods (CPG) industry.
- Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms. - Familiarity with Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation) is a plus. - Ability to collaborate cross functional teams and provide tech mentorship to other stakeholders
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Already applied? Track this application
Yes. We’ve followed one other D&T Machine Learning Engineer II job there since October 2026. It came down after 7 days.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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 an ML Engineer(Agentic) to join the D&T Global Artificial Intelligence and Automation (AIA) Organization as part of the overall AIA Engineering group. 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.
In this role, you are a critical member of the AIA team focused on leading efforts dedicated to enabling, optimizing, and scaling our next-generation agentic AI platforms. The candidate will be instrumental in designing and implementing robust custom connectors, ensuring seamless and secure API integrations, and orchestrating complex agent behaviors to unlock new business capabilities.
We are looking for an individual with a strong background in Generative AI and Agentic AI, coupled with a passion for developing, maintaining, and continuously enhancing intelligent systems that deliver significant business value and drive innovation across the enterprise.
KEY ACCOUNTABILITIES
MINIMUM QUALIFCATIONS
Experience & Education:
Technical Skills:
Soft Skills:
PREFERRED QUALIFICATIONS
ELIGIBILITY
Applicants must meet minimum age qualifications in the country in which the job is located.
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Powai, Mumbai, MH
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