AI Production Support Engineer

This role is a senior Production Support position with a strong focus on applying Artificial Intelligence to improve operational efficiency, incident response, and root cause analysis within the Credit trading platform.

The primary goal of the role is to understand existing production issues, investigation patterns, and support workflows, and to design and build AI-powered tools and solutions that reduce mean time to detection (MTTD), mean time to resolution (MTTR), and overall operational toil.

The role sits at the intersection of production support, software engineering, and AI enablement, partnering closely with Development, QA, and Business teams to modernize how production issues are identified, analyzed, and resolved.

Tradeweb Technology jobs are fully remote. The Tradeweb Technology hub is located in our Jersey City office which can be used for team meetings and collaboration efforts. There may be days where travel to the Jersey City office is recommended for organizational off‑sites.

• Analyze historical production incidents and ticket data to identify recurring patterns, investigation paths, and bottlenecks.
• Design and build AI‑assisted tools to:
• Accelerate root cause identification
• Summarize logs, alerts, and metrics
• Suggest likely failure domains or components
• Assist with incident triage and prioritization
• Partner with Production Support engineers to embed AI into day‑to‑day workflows, not as standalone experiments.
• Develop internal tools, scripts, or lightweight services that leverage AI models to improve support efficiency.
• Apply AI coding assistants to rapidly prototype, iterate, and product ionize operational tooling.
• Document AI‑driven workflows, playbooks, and best practices for use by the wider support organization.
• Measure and track impact of AI adoption (reduction in MTTR, investigation time, manual effort).
• Provide extremely high levels of availability and stability for production, demo, and test environments supporting Credit trading.
• Perform deep dives into application logs, metrics, and codebases to understand system behavior and failure modes.
• Support monitoring, alerting, and observability platforms (e.g., logs, dashboards, alerts).
• Work with development team and AI teams, to partner in building out new AI related features in AI.

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• 10+ years of overall IT experience, with significant experience in Production Support or Site Reliability roles or Dev Ops roles.
• Strong hands‑on experience supporting large‑scale, highly available financial or trading systems with complex architecture, distributed systems and system troubleshooting.
• Solid programming background with experience in one or more of:
• C++ Python
• Node.js
• Scripting languages (Shell, Bash, Perl)
• Experience working with:
• Logging and monitoring tools (e.g. Coralogix, Grafana)
• Containers and orchestration (Docker, Portainer)
• Messaging/streaming platforms (e.g., Kafka)
• Databases (relational and non‑relational)
• Excellent communication skills and ability to work with technical and non‑technical stakeholders.

• Hands‑on experience using AI coding and assistant tools to build/​enhance software solutions.
• Practical experience applying AI to:
• Code analysis
• Log analysis
• Automation
• Workflow optimization
• Building MCP servers & AI Agents
• Familiarity with modern AI tooling ecosystems; preferred tools include:
• OpenAI
• Claude
• Cursor
• Ability to evaluate AI‑generated outputs critically and apply them safely in production environments.
• Experience building small internal tools, scripts or services that improve operational productivity.

• Understanding of source control systems (e.g., Git) and collaborative development workflows.
• Familiarity with ticket management systems such as Service Now and Jira, especially for analyzing historical incidents.
• Networking knowledge, including TCP/UDP, multicast, and packet analysis tools (e.g., Wireshark).
• Experience operating in regulated or security‑conscious environments.
• Fixed income or bond trading domain knowledge.
• Exposure to AI enablement, developer productivity, or…