Senior Manager - Data Science

Company:

Marsh Corporate

Description:

We are seeking a talented individual to join our Tech Team(TE2A), a Marsh business]. This role will be based in Pune/Mumbai/Gurgaon/Noida. This is a hybrid role that has a requirement of working at least three days a week in the office.

We are seeking a highly skilled AI Engineer with deep expertise in agentic AI frameworks and production deployment. The ideal candidate will have hands-on experience with LangChain and LangGraph V1 frameworks, designing advanced memory management systems, and operationalizing large language models (LLMs) at scale. This role requires a strong background in data modeling, ETL processes, and container orchestration to build robust, scalable AI products.

We will count on you to:

• Develop, deploy, and maintain agentic AI products using LangChain and LangGraph V1 frameworks in production environments.
• Design and implement sophisticated memory management systems for both short-term and long-term agentic memory.
• Architect and operationalize evaluation frameworks and observability tools, including implementing LLMs as judges at scale in production.
• Design and manage relational and non-relational data models; develop and implement ETL pipelines leveraging Databricks.
• Build, deploy, and manage containerized applications using Kubernetes to ensure scalable and reliable AI services.
• Continuously monitor and optimize AI system performance, reliability, and scalability.
• Lead the ideas when it comes to machine learning and AI.Responsible for communicating complex data in a simple and actionable way.Manages the day-to-day operations of junior staff members.
• Ensures individual and team responsibilities are performed in a timely, consistent, responsive manner.
• Provides ongoing performance feedback to team members, including the mid-year/year-end formal Performance Management process; as well as when progressive counseling is required. Monitors trends in individual/teams performance daily, weekly, and monthly.

What you need to have: 

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Preferred Bachelor’s or Masters in AI/ML
• 10+years of experience
• Proven experience with LangChain and LangGraph V1 frameworks, including developing and deploying agentic AI products.
• Strong expertise in designing memory management architectures for agentic AI, covering both short-term and long-term memory.
• Demonstrated experience in designing and implementing evaluation (evals) and observability systems, with operationalizing LLMs as judges at scale.
• Deep knowledge of relational and non-relational data models.
• Hands-on experience with ETL development and implementation using Databricks.
• Advanced skills in building and deploying containerized applications using Kubernetes.
• Strong programming skills in Python and familiarity with AI/ML frameworks and tools.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Experience with cloud platforms such as AWS, Azure.
• Familiarity with CI/CD pipelines and infrastructure as code.
• Background in AI ethics, fairness, and responsible AI deployment.
• Prior experience in financial services or risk management industries.
• Lead the ideas when it comes to machine learning and AI.Responsible for communicating complex data in a simple and actionable way.Manages the day-to-day operations of junior staff members.
• Ensures individual and team responsibilities are performed in a timely, consistent, responsive manner.
• Provides ongoing performance feedback to team members, including the mid-year/year-end formal Performance Management process; as well as when progressive counseling is required. Monitors trends in individual/teams performance daily, weekly, and monthly.

What makes you stand out?

• Candidates must possess full professional proficiency in both written and spoken English
• Strong problem-solving and troubleshooting skills.
• Strong communicator, in both verbal and written form, able to articulate concepts and ideas, break through barriers, engage people, and work effectively with others under pressure.
• Neutral toward technology, vendor, and product choices more interested in results than in personal preferences.
• Unflappable in the face of opposition to ideas

Why join our team:

• We help you be your best through professional development opportunities, interesting work and supportive leaders.
• We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
• Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit corporate.marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.