Major Incident and Problem Manager, Associate

Team Overview

The Service Management team provides industry‑standard Incident, Problem and Change Management, alongside infrastructure operational support for Aladdin. We operate using modern engineering practices and tooling, including ServiceNow and AI‑enabled workflows, and measure outcomes through clear operational metrics.

Incident Management is responsible for restoring service during production incidents and driving scalable stability improvements across BlackRock and its Aladdin clients.

BlackRock operates a 24/7 Major Incident Management function supporting global clients across Europe, the Americas, Asia Pacific and India. This role is based in Edinburgh and is required to cover core European hours between 09:00 and 18:00, Monday to Sunday, with rotational weekend working.

Role

We are seeking an experienced Incident & Problem Manager (5+ years) with a strong passion for technical troubleshooting and the ability to lead multiple simultaneous incidents.

This role exists to deliver rapid time to detect and time to resolve, and to eliminate repeat incidents at a system level by operating an AI‑first incident delivery model. The Major Incident & Problem Manager is accountable for turning incidents into measurable stability improvements—particularly those caused by change—and for building an incident operating rhythm where AI handles correlation, classification and narrative generation by default, allowing humans to focus on decision quality, trade‑offs and prevention.

In complex distributed platforms, incidents are often slowed by manual triage, fragmented ownership and time‑consuming coordination. This role addresses those challenges by creating a decision‑centric incident response model, powered by AI‑driven signal correlation and automation‑first execution, ensuring that:

• The right responders are engaged faster

• The most likely causes are identified sooner

• Mitigation decisions are taken with clearer risk framing

• Communications remainaccurate and timely

• Repeat failures are systematically removed rather than documented

The role partners closely with Engineering and SRE / DevOps teams, leveraging automation, observability tooling and emerging AI‑driven insights. The successful candidate will have a DevOps mindset, be able to actively troubleshoot, and utilise and enhance AI and automation.

The role also includes participation in continuous improvement initiatives aimed at improving the stability, performance and resilience of the Aladdin platform, and enhancing Service Management services.

Key Responsibilities

1. Lead major incidents as a decision authority (P1–P4)

• Lead end‑to‑end management of production incidents, including investigation, recovery execution and closure

• Run incidents as a decision system, driving clarity on what is known, what is suspected and what action is taken next

• Manage multiple simultaneous incidents while maintaining consistent prioritisation and escalation

2. Operate an AI‑first incident workflow (human‑validated, human‑overridden when required)

• Triage and categorise incidents using AI‑driven classification, with human validation and override where appropriate

• Drive AI‑automated ticket routing and apply risk‑based escalation judgement when automation is insufficient

• Ensure incident timelines and summaries are produced to a high standard using AI‑generated artefacts, correcting them where required

3. Supervise automated remediation and agentic responders

• Supervise automated remediation and agentic responders, intervening to pause, override or redirect when risk requires

• Ensure automated remediation is safe, auditable and aligned with service ownership and operational readiness

4. Manage a robust Problem Management process to prevent incident recurrence

• Ensure root causes and preventative actions are clearly captured and translated into an effective Problem Management process

• Identify incident trends and repeat patterns, driving scalable remediation to reduce recurrence

• Partner with Engineering and SRE / DevOps to embed learnings into automation, observability, runbooks and readiness controls

• Design, build and actively maintain a Known Error Database that functions as a real‑time operational asset

• Work with product teams to design, build and deliver a meaningful process for addressing repeat incidents

5. Deliver executive‑grade communications (AI‑drafted, human‑approved)

• Validate, approve and issue regular communications that are concise, informative and appropriate for stakeholders

• Ensure communications accurately reflect impact, mitigation progress, key risks and confidence‑based ETAs

6. Drive continuous service improvement and regulatory alignment

• Drive process and tooling changes that support operational resilience and regulatory requirements, including DORA and GDPR, where applicable

• Provide input and ownership for continual service improvement initiatives, with a primary focus on Agentic AI and its application to Incident Management

Required Experience and Capabilities (Must Have)

• 5+ years’ experience in Incident and Problem Management within a production environment supporting business‑critical platforms

• Strong technical troubleshooting capability, with the ability to engage credibly with engineers during complex failures

• Proven ability to lead multiple simultaneous incidents and drive structured recovery under pressure

• DevOps mindset, with comfort using observability tooling, automation and operational engineering practices

• Ability to produce clear, high‑quality communications suitable for senior stakeholders

• Experience operating AI systems for triage, correlation and narrative generation, with sound judgement on when outputs require validation or override

• Ability to translate repetitive incident activity into automation requirements and drive adoption with engineering partners

Advantages / Desirable Qualities

• Experience working in or with FinTech or regulated environments

• Knowledge of cloud platforms such as Azure and/or AWS, and understanding of IaaS / PaaS / SaaS service models

• Experience with Microsoft Copilot and AI‑enabled productivity tooling

• Programming capability (e.g. Python) to automate common tasks or prototype improvements

• Familiarity with configuration management, deployment and orchestration tooling (e.g. Ansible)

• Strong data analysis skills using tools such as Splunk, Grafana, Tableau, Excel and/or Power BI

• Strong experience with ServiceNow and operational reporting