Application Support Specialist supporting AI and business applications for Marsh, a global risk and management consulting company. Monitoring systems, troubleshooting incidents, and delivering technical solutions across hybrid Canadian teams.
Responsibilities
Support production and business applications, monitor application health, and proactively identify and escalate issues
Handle user-facing production issues, requests, and data or information needs
Support AI applications through triage, debugging, and troubleshooting
Maintain understanding of applications, processes, and stakeholders while supporting online business teams
Triage and clarify incident and service-request tickets with onshore and offshore stakeholders
Analyze tickets, coordinate with IT teams, and implement technical solutions for software and usability issues
Monitor application and server health, logs, and alerts; escalate issues and validate fixes through stakeholder testing
Perform root cause analysis for high-priority incidents and prepare incident reports
Communicate updates about tickets, deployments, outages, and changes; develop client communications for rollouts, downtime, functionality, training, and documentation
Ensure adherence to SDLC, change-management, implementation, and support processes
Produce service-management summary reports and contribute to process and application improvements
Provide on-call and off-hours support, including weekends, and accommodate off-hours conference calls
Analyze incident data and logs to identify patterns and improvement opportunities
Manage improvisation projects in Application Support and participate in ideation and gigs
Requirements
Degree in Computer Science or Information Technology
At least 2 years of experience in AI application support
Monitoring experience with Datadog and LangSmith tools
Hands-on support and development experience with one or more of MEAN/MEARN stack, PostgreSQL, MS SQL Server, REST/JSON/GraphQL APIs, Postman/Bruno, and GitHub
Scripting knowledge of Python
Practical experience with Docker and/or Kubernetes containerization and orchestration
Experience supporting multi-tier Internet/Intranet applications using common design patterns
Strong understanding of API principles including HTTP methods, REST, JSON, SOAP, and GraphQL
Familiarity with Apigee and AWS API Gateway
Experience with ITSM and monitoring tools such as ServiceNow, JIRA, Datadog, or Splunk
Minimum one year of AI monitoring experience with Datadog or LangSmith
Understanding of traditional and LLM AI models, model lifecycle, bias/accuracy, and model drift
Knowledge of prompt engineering, MCP, RAG, token management, and AI KPIs
Excellent English communication skills
Strong debugging, troubleshooting, analytical, and design capabilities
Strong track record of process optimization
Organizational and time-management skills, ability to learn quickly, quality consciousness, and commitment to deadlines
Availability for on-call and off-hours support, including weekends
ITIL certification, AWS/Azure cloud knowledge, and offshore-onsite delivery experience are stand-out qualifications
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