Trader Intelligence Engineer

Shell•Houston, TX

1d•Onsite

About The Position

Shell is seeking a Trader Intelligence Engineer to join its team in Houston, TX. This role leads and continuously improves the integration, operation, and transformation of a large, complex IT estate supporting a global energy trading business. Working as part of a global team, it is a key part of transforming the trader experience Shell ecosystems and positioning Trading for the Future. The role creates business value through operational stability, automation, and intelligent observability. The role designs, implements, and scales AIOps and AI‑enabled operational capabilities, leveraging internal automation and AI platforms to improve productivity, accelerate incident resolution, and automate IT operations for the trading floor. This includes building and operating use cases such as anomaly detection, predictive maintenance, intelligent alerting, root cause analysis, and self-healing workflows, while ensuring strong governance, risk management, security, and ethical use of AI. The role also automates operational processes and reconciliations using industry-standard AI and observability tools across the whole delivery stack. It monitors and optimizes AI system performance and translates operational data into actionable insights. In addition, it leads to the adoption of observability tools, service-to-desk and desk-to-application mapping, contextualized alerting, and service health visualization to improve situational awareness and trader outcomes. A key focus of the role is enhancing the trader experience by engaging effectively with enterprise service teams, developing the "detection brain," defining alerting and self-healing rules, continuously improving trader outcomes, and embedding AI-driven operations as a core capability across Trading & Supply Core Services and broader teams.

Requirements

Must have legal authorization to work in the US on a full-time basis for anyone other than current employer
Bachelor’s degree
At least 8 years of experience in production support, infrastructure operations, application support, or service operations, including at least 3 years of experience with AIOps solutions or AI-enabled operations
Experience supporting energy trading, commodity trading, financial trading, or trading floor environments is preferred
Demonstrated hands-on experience with one or more of the following platforms: Dynatrace, Aternity, SolarWinds, Grafana, ThousandEyes, Azure Monitor, Graylog, and/or Kafka
Experience working within Microsoft Azure environments
Demonstrated ability and interest in working effectively in a high-pressure, fast-paced trading floor environment

Responsibilities

Resolve issues affecting trading-critical services, hybrid infrastructure, and supplier-supported platforms
Support complex and time-sensitive incidents by applying sound technical judgment, clear decision-making, and effective major incident management
Help manage change activity, vulnerabilities, and operational risks that could impact trading operations
Improve the end-to-end trader and stakeholder experience by partnering with business stakeholders, global support teams, enterprise teams, and vendors
Design, build, and operate AIOps capabilities such as anomaly detection, predictive maintenance, root-cause analysis, intelligent alerting, and self-healing workflows
Lead observability strategy, service mapping, operational intelligence, service-health views, desk-to-application mappings, contextual alerts, and alerting frameworks across trading-critical services
Use observability and monitoring tools such as Dynatrace, Aternity, SolarWinds, GrayLog, Azure Monitor, ThousandEyes, Kafka, Grafana, and related platforms to improve service reliability and visibility
Develop automation solutions using AI, Python, PowerShell, machine learning, ML Ops, Microsoft 365, Power Apps, Power Automate, and Copilot Studio to improve operational efficiency
Work with Azure technologies such as ADF, Storage Containers, Databricks, SQL, and Cosmos DB to support automation and data-driven operations
Utilize telemetry, user experience, operational data, KPIs, and AI outcomes to proactively identify risks and improve service reliability, efficiency, and trader experience
Evaluate, prototype, and adopt internal automation, AI, Agentic AI, AI Foundry, LLMs, Copilot Studio, and front-end tools such as React through practical proofs of concept
Drive adoption of AIOps across the Trading & Supply Core Services team and embed AI-enabled operations as a core capability
Lead Trader 360 engagement across the Americas and coordinate with other regions to improve the global trader experience