Senior Manager – Applications Development

Marsh McLennan

. Design, build, and scale AI-enabled applications that drive business value and enhance client experience .

Posted 10/5/2026full-timePune • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI-enabled applications and multi-agent architectures, with a strong focus on Python development and integration of LLM platforms. Proven ability to lead complex technical delivery while ensuring compliance with governance and security standards.

Highest-signal resume keywords

AI-Enabled Application DevelopmentMulti-Agent Architecture DesignPython ProgrammingLangChain and LangGraph UtilizationSoftware Development Lifecycle Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Application DesignMulti-Agent SystemsPython DevelopmentTool-Calling AgentsFunction-Calling AgentsMemory-Enabled AgentsAutomated TestingCI/CD ImplementationPerformance MonitoringAgent Behavior Specification

Soft Skills

Excellent Communication SkillsTroubleshooting SkillsIndependent Work Ability

Tools & Technologies

LangChainLangGraphDSPyAPIsVector DatabasesWorkflow EnginesEnterprise Data Platforms

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's in Data Science

Industry Keywords

Agentic ArchitectureGovernance FrameworksCompliance StandardsFinancial ServicesAuditability and Explainability

Tech Stack

Tools & technologies

PythonSDLC

About the role

Key responsibilities & impact

Design, build, and scale AI-enabled applications that drive business value and enhance client experience
Lead the development of agentic AI solutions
Establish engineering standards and mentor teams in modern AI development practices
Strengthen delivery discipline across architecture, engineering, governance, and the software development lifecycle
Lead US/Canada payroll projects and work on multiple assignments
Design and deliver AI-enabled applications and agentic systems in production
Build multi-agent architectures using planner, executor, reviewer, critic, and supervisor patterns
Develop tool-calling, function-calling, and memory-enabled agents
Use LangChain, LangGraph, DSPy, and prompt engineering for orchestration and optimization
Build production-grade AI services in Python
Integrate LLM platforms, vector databases, enterprise platforms, APIs, workflows, events, and data services
Implement observability, evaluation, tracing, decision logging, and performance monitoring
Work within governance, security, privacy, and compliance frameworks
Lead complex technical delivery across engineering, product, business, risk, and compliance teams

Requirements

What you’ll need

Bachelor's degree in Computer Science or Master's 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 experience
Experience designing and implementing modern multi-agent AI architecture
Experience building planner, executor, reviewer/critic, and supervisor agent patterns
Experience developing tool-calling, function-calling, and memory-enabled agents
Experience using LangChain and LangGraph for orchestration, workflow control, and agent coordination
Experience applying DSPy and prompt optimization techniques
Experience defining reusable agent contracts, interfaces, and schemas
Experience designing hierarchical, collaborative, and event-driven agent workflows
Experience leading delivery across the full software development lifecycle, including an Agentic SDLC
Experience creating agent behavior specifications, prompt and policy versioning, and offline evaluation frameworks
Experience implementing automated testing for agent workflows and guardrails
Experience supporting controlled rollout, telemetry-driven improvement, and continuous optimization
Experience building production-grade AI services primarily in Python
Experience integrating LLMs, vector databases, APIs, workflow engines, and enterprise data platforms
Experience implementing CI/CD for agent code, prompts, and policies
Experience implementing tracing, decision logging, tool monitoring, and failure analysis
Experience applying evaluation methods for hallucination detection, consistency, and fitness scoring
Experience designing human-in-the-loop feedback mechanisms
Experience monitoring and optimizing cost, latency, throughput, and behavioral drift
Experience designing AI solutions aligned with financial services and enterprise governance expectations
Experience ensuring auditability, explainability, privacy, security, and resilience
Experience embedding guardrails to reduce hallucination risk, bias, unauthorized actions, and escalation failures
Experience producing documentation for compliance, internal audit, and regulatory review
Minimum 12 months experience as Manager/Senior Manager
Should have at least “On track” or above in last appraisal
Should not be under any Performance Continuity Plan or have had any official Disciplinary action within the last 3 months
Should not have applied for any other IJP within Marsh McLennan in the last 3 months
Excellent verbal and written communication skills
Good troubleshooting and technical skills
Able to work independently

Benefits

Comp & perks

Professional development opportunities
Interesting work
Supportive leaders
Vibrant and inclusive culture
Career opportunities
Benefits and rewards to enhance well-being