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Principal Engineer – Core Cloud Platform

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Remote from
UK
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
21 Nov 2026
Listing views
34
Application actions
2
Application toolkit

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AI Summary

The role, at a glance.

AlphaSense seeks a Principal Engineer to define and evolve the core AWS, Kubernetes, networking, and storage platform supporting hundreds of services and more than 400 engineers. The role leads the transition to a cell-based architecture, including automated cell provisioning, a shared cell registry, and reusable cross-cell control mechanisms. It requires deep operational and software engineering expertise across large Kubernetes fleets, cloud infrastructure, databases, service meshes, CI/CD, Python, and Go. The engineer will set technical direction across many teams while improving reliability, security, cost efficiency, self-service capabilities, and AI-enabled infrastructure workflows.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a principal-level platform architecture role spanning hundreds of Kubernetes clusters, multi-region infrastructure, storage systems, and organisation-wide technical standards. Success requires both hands-on production expertise and the influence to align senior engineers and engineering leaders across dozens of teams.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$220,000
US market range (per year)$185k–$260k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer compensation is disclosed. Estimated annual market compensation is shown in USD for a principal cloud-platform engineer with large-scale Kubernetes, AWS, and distributed-systems ownership; this is an AI estimate, not employer-provided pay.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a cell-based platform architecture that can scale from dozens to hundreds of Kubernetes clusters?

I would establish a versioned cell specification that separates platform configuration from application code, then build an automated provisioning pipeline around reusable infrastructure modules and validated cluster baselines. A central registry would track cell capabilities, versions, ownership, and lifecycle state, while shared control-plane patterns would enforce consistent policy, observability, security, and upgrade processes.

Describe your approach to operating Kubernetes reliably across a large fleet of clusters.

I focus on standardised cluster blueprints, declarative GitOps delivery, progressive rollouts, fleet-wide observability, and automated lifecycle workflows. Upgrades, patching, policy enforcement, and incident response should be repeatable operations with clear health gates, rollback paths, and measurable service-level objectives.

How do you balance platform standardisation with the needs of independent product teams?

I define opinionated paved roads for the common cases, including deployment templates, Helm charts, identity, networking, secrets, monitoring, and data-service integrations. Teams retain flexibility through documented extension points, but deviations should have an explicit technical justification, ownership model, and lifecycle plan to prevent unmanaged duplication.

What factors would guide your design of cloud-side configuration and Helm chart ownership?

I would keep environment and platform concerns separate from service-owned application configuration, use strongly versioned interfaces, and apply validation before changes reach production. The chart layer should provide secure defaults, support controlled customization, include policy checks, and enable safe progressive deployment across cells.

How would you use AI tooling to improve infrastructure engineering without weakening reliability or security?

I would apply AI to assisted troubleshooting, runbook discovery, configuration review, incident summarisation, and developer self-service, while retaining deterministic controls for production changes. AI-generated actions should be constrained by policy, auditable, tested in non-production environments, and subject to appropriate approval gates for higher-risk operations.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

About AlphaSense:

AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster, more confident decisions in business and finance. The platform combines domain-specific AI with a vast content universe of over 500 million premium business documents — including equity research, earnings calls, expert interviews, filings, news, and internal proprietary content. Purpose-built for speed, accuracy, and enterprise-grade security, AlphaSense helps teams extract critical insights, uncover market-moving trends, and automate complex workflows with high-quality outputs. With AI solutions like Generative Search, Generative Grid, and Deep Research, AlphaSense delivers the clarity and depth professionals need to navigate complexity and obtain accurate, real-time information quickly. For more information, visit www.alpha-sense.com. Come join us.

About the Role:

The Core Cloud Platform team is responsible for AlphaSense’s entire cloud infrastructure, including AWS account management, networking, data storages, and Kubernetes clusters. We build the underlying platform that supports hundreds of services and is used by over 400 globally distributed engineers.

We’re scaling into a cell-based architecture, and the number of cells we run is growing fast, taking our Kubernetes footprint from dozens of clusters toward hundreds. That takes the platform in three directions at once: infrastructure configuration becomes a first-class layer with its own lifecycle, independent of application code; provisioning a new cell becomes a days-long automated operation rather than a multi-week effort; and cross-cell control points become standard, reusable, and consistent everywhere.

This is a Principal Engineer role with real breadth within the cloud platform. You’ll set the architectural roadmap for our cloud, Kubernetes, and storage platform as it scales with AlphaSense’s growth, and take dedicated ownership of the cloud-side configuration and Helm chart layer that every service depends on. Data storages are a critical part of this surface, and we’re looking for genuine depth there.

It requires a deep cloud of both operational and software development skills, the ability to lead ambitious technical programmes, and the credibility to set direction with Engineering leaders and very senior engineers across dozens of teams.

We’re looking for someone who genuinely embraces AI tooling in their day-to-day work, appreciates the productivity value it brings, and is motivated to make our infrastructure ever-more AI friendly.

What You’ll Do:

  • Own the architectural roadmap for our cloud, Kubernetes, and storage platform
  • Own cloud-side configuration and the Helm chart layer for Cloud Core
  • Build the cell registry and automate provisioning to take new cell setup from weeks to days
  • Design the cross-cell gate mechanism as the reusable standard checkpoint across every cell
  • Own, operate and evolve our Cloud and Kubernetes platform, including our data storage layers
  • Make operations (upgrades, patching, lifecycle management) routine across hundreds of clusters
  • Continuously improve the security, reliability, cost efficiency and performance of our infrastructure
  • Champion standards and drive initiatives to promote uniformisation and eliminate duplication
  • Enable truly self-service and agentic workflow patterns that support a Build it – Own it model
  • Build tooling and AI powered integrations that reduce the cognitive load in cloud
  • Architect, design and implement simple and maintainable solutions

Who You Are:

  • Extremely experienced in Kubernetes and its various components, containerisation and AWS cloud
  • Proven track record of running Kubernetes and Cloud based production SaaS systems at scale
  • Experience operating Kubernetes as a large fleet with hundreds of clusters
  • Strong knowledge of data storages across SQL, MongoDB, ClickHouse and Elasticsearch
  • Strong operational and troubleshooting skill with Kubernetes, databases and messaging systems
  • Deep understanding of networking and production level usage of service meshes and gateways
  • Experience separating infrastructure configuration from application code at scale
  • Experience with cell-based, multi-tenant or multi-region architectures
  • Proficiency in Python and Golang
  • Evangelist of highly performant CI/CD practices that are supportive of agentic workflows
  • Ability and desire to design, lead, influence and deliver on ambitious technical roadmaps

Nice to have:

  • Experience with Vespa
  • Automated provisioning of new environments, regions or cells end-to-end
  • Management of large fleets of Kubernetes clusters with lifecycle management tools
  • Production usage of Hashicorp Vault or similar secret management systems

AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.

In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.

Recruiting Scams and Fraud

We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note:

  • AlphaSense never asks candidates to pay for job applications, equipment, or training.
  • All official communications will come from an @alpha-sense.com email address.
  • If you’re unsure about a job posting or recruiter, verify it on our Careers page.

If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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