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

Overview

Serve as a Sr. ML Engineer (Agentic Engineer) within the D&T AI and Automation organization, building and operationalizing enterprise-level Agentic AI and ML platforms, scalable solution pipelines, and Agentic workflows for business-impacting problem statements.

What you'll do

• Lead the technical enablement, integration, and continuous enhancement of advanced agentic AI platforms and workflow designs in line with performance, scalability, reliability, and security standards.
• Evaluate new agentic-first platforms, tools, and frameworks.
• Architect, design, develop, and implement custom connectors and integration solutions for data sources, enterprise applications, and external services.
• Drive the design, development, and rigorous testing of APIs for secure, reliable, and efficient integration with internal and external systems.
• Develop, implement, and optimize strategies for orchestrating complex agent workflows, inter-agent communication, and decision-making processes.
• Collaborate with engineering teams to establish, implement, and support monitoring and observability capabilities for Agentic workflows across multiple platforms.
• Use agent telemetry, feedback loops, success metrics, cost and latency dashboards to evaluate agent quality, safety, and ROI and tune prompts, tools, and workflows.
• Research, operationalize, and standardize ML tooling and processes, including installation, maintenance, documentation, and best practices.
• Conduct platform optimization, performance tuning, lifecycle management, bug fixes, security patches, and capacity planning.
• Develop and lead solution prototypes from ideation and scoping through implementation and future road mapping with internal and vendor-led teams.
• Provide advanced technical support and expert-level troubleshooting, perform root cause analysis, and implement preventative measures.
• Create and maintain technical documentation for platform architecture, custom connectors, API specifications, and operational procedures.
• Help develop and establish governance best practices and enterprise standards for Agentic tooling and solutions.
• Ensure platform development and integrations follow enterprise security policies, data privacy regulations, and compliance standards.
• Continually develop knowledge and skills through formal training, reading, conferences, and meetups.

What you'll need

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Software Engineering, Artificial Intelligence, or Data Science, or a closely related technical field.
• 5-8 years of progressive experience in software engineering, platform development, or a related technical field, focused on building scalable and resilient systems.
• 1-2 years of hands-on, in-depth experience with Generative AI and Agentic AI technologies, platforms, and frameworks.
• Proven experience designing, developing, and deploying complex integrations and custom connectors for enterprise-level applications.
• Expert-level proficiency in at least one modern programming language such as Python, Java, or Go.
• Deep understanding and extensive experience with API design principles, development, and rigorous testing, including RESTful APIs, GraphQL, and gRPC.
• Expertise in building custom connectors and integrating enterprise applications such as Salesforce, SAP, and ServiceNow with diverse data sources.
• Good understanding or 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 and their AI/ML services.
• Proficiency with monitoring, logging, and observability tools such as Prometheus, Grafana, ELK stack, Datadog, or Splunk.
• Working knowledge of MCP connections, RAG, vectors, embeddings and indexing, knowledge graphs, and OAuth flows.
• Strong understanding of CI/CD.
• Strong understanding of orchestration frameworks such as Airflow and Kubeflow.
• Exceptional problem-solving and analytical capabilities, attention to detail, and a proactive approach to complex technical challenges.
• Strong communication and collaboration skills, including the ability to explain technical concepts to technical and non-technical stakeholders.
• Ability to work independently and as a key contributor within cross-functional teams in a fast-paced, dynamic environment.
• Passion for learning new technologies and solving challenging problems.
• Ability to mentor others and lead the team in technology and best practices.

Nice to have

• Understanding of the Consumer-Packaged Goods industry.
• Familiarity with AI/ML lifecycle stages and MLOps concepts.
• Background building, maintaining, and supporting traditional ML pipelines in a GCP environment.
• 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 such as Docker and Kubernetes and orchestration platforms.
• Familiarity with Infrastructure as Code tools such as Terraform and CloudFormation.
• Ability to collaborate with cross-functional teams and provide technical mentorship to stakeholders.
• Strong leadership potential, including the ability to mentor junior engineers and drive best practices.
• Working experience with Generative and Agentic AI ecosystems on a hyperscaler such as Google Cloud Platform or Amazon Web Services.
• Google Cloud Platform and Vertex AI experience.

Details

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