Marsh McLennan—Senior Manager - Applications Development

Job description

Description: We are seeking a talented individual to join our MMA team at Marsh. This role will be based in Pune/Mumbai/Gurgaon. This is a hybrid role that has a requirement of working at least three days a week in the office. As an AI Specialist, you will design, build, and scale AI-enabled applications that drive business value and enhance client experience. You will lead the development of agentic AI solutions, establish engineering standards, and mentor teams in modern AI development practices. You will also help strengthen delivery discipline across architecture, engineering, governance, and the software development lifecycle. We will count on you to: - Lead US/Canada payroll Projects and ability to work on multiple assignments. - Designing and delivering AI-enabled applications and agentic systems in production - Building multi-agent architectures, including planner, executor, reviewer, critic, and supervisor patterns - Developing tool-calling, function-calling, and memory-enabled agents - Using LangChain, LangGraph, and similar frameworks for orchestration and workflow design - Applying DSPy, prompt engineering, and optimization techniques to improve quality and repeatability - Building production-grade AI services in Python - Integrating with leading LLM platforms such as Anthropic, OpenAI, and open-source models - Designing RAG solutions using vector databases such as Pinecone, FAISS, Milvus, or Weaviate - Integrating AI systems with enterprise platforms through APIs, workflows, events, and data services - Implementing observability, evaluation, and optimization for AI systems, including tracing, decision logging, and performance monitoring - Working within governance, security, privacy, and compliance frameworks, ideally in regulated industries - Leading complex technical delivery while collaborating effectively across engineering, product, business, risk, and compliance teams What you need to have: - Bachelor's degree in Computer Science or Masters in Data Science, related field, or equivalent experience - Overall 10+ years of technology experience, including delivery of scalable, resilient digital products Agentic architecture and platform design - Design and implement modern multi-agent AI architecture - Build planner, executor, reviewer/critic, and supervisor agent patterns - Develop tool-calling, function-calling, and memory-enabled agents - Use LangChain and LangGraph for orchestration, workflow control, and agent coordination - Apply DSPy and prompt optimization techniques for performance, consistency, and regression control - Define reusable agent contracts, interfaces, and schemas - Design hierarchical, collaborative, and event-driven agent workflows AI engineering and delivery - Lead delivery across the full software development lifecycle, including an Agentic SDLC - Create agent behavior specifications, prompt and policy versioning, and offline evaluation frameworks - Implement automated testing for agent workflows and guardrails - Support controlled rollout, telemetry-driven improvement, and continuous optimization - Build production-grade AI services primarily in Python - Integrate LLMs, vector databases, APIs, workflow engines, and enterprise data platforms - Implement CI/CD for agent code, prompts, and policies Observability and optimization - Implement tracing, decision logging, tool monitoring, and failure analysis - Apply evaluation methods for hallucination detection, consistency, and fitness scoring - Design human-in-the-loop feedback mechanisms - Monitor and optimize cost, latency, throughput, and behavioral drift Governance, risk, and compliance - Design AI solutions aligned with financial services and enterprise governance expectations - Ensure auditability, explainability, privacy, security, and resilience - Embed guardrails to reduce hallucination risk, bias, unauthorized actions, and escalation failures - Produce documentation to support compliance, internal audit, and regulatory review What makes you stand out: - Excellent verbal and written communication skills, comfortable interfacing with business users - Good troubleshooting and technical skills - Able to work independently 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 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. Skills: ai architecture, multi-agent systems, python, langchain, langgraph, dspy, prompt engineering, vector databases, api integration, workflow orchestration, observability, performance monitoring, ai governance, ai compliance, ai security, ai privacy, ai risk management, ai evaluation, ai optimization, ai sdlc, agent behavior specification, prompt versioning, offline evaluation frameworks, automated testing, ci/cd, tracing, decision logging, ai auditability, ai explainability, ai resilience