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Volta

Financed AI data centers and infrastructure

Senior Internal Automation Engineer

AI Application Engineering +1Updated on Nov 14
Full-time

About the Job

Requirements

  • Production software development experience at the standard of an engineering team, rather than operational scripting.
  • Fluency across multiple software ecosystems and ability to use the language, runtime, and software development kit suited to each problem; Python and Go are common but not required.
  • Practical experience with third-party application programming interfaces, including pagination, rate limits, idempotency, retries, webhooks, and integration failure handling.
  • Command of OAuth 2.0, OpenID Connect, service accounts, application programming interface keys, and secret management.
  • Disciplined engineering practices including source control, code review, automated testing, controlled deployment, and separation between building and releasing changes.
  • Hands-on experience building with large language models, including tool use and structured extraction, and judgment about when not to use a model.
  • Hands-on experience with agentic patterns, including tool and function calling, model context protocol or equivalent tool interfaces, state and retry handling across multi-step runs, and testing agent behavior against realistic cases before production deployment.
  • Working awareness of rules governing artificial intelligence and automated decision-making in workplace contexts, including identifying use cases that require legal review before development.
  • Ability to understand a business process by working with a subject matter expert and translate it into a correct implementation without requiring the expert to specify the solution.
  • A track record of building reliable, secure, auditable systems rather than one-off demonstrations.
  • Ability to independently prioritize work and own outcomes.

Responsibilities

  • Automate finance operations by ingesting received invoices into banking and bookkeeping systems, classifying and matching them, and resolving exceptions.
  • Work with process owners across finance, information technology, People, and delivery to turn described workflows into specified, testable automations.
  • Work within Corporate IT, review colleagues' changes, have one's own changes reviewed, and align automation with administration of underlying systems.
  • Build and operate integrations with Microsoft Graph, Slack, Atlassian, banking platforms, and human resources and identity tools.
  • Own authentication and integration credentials, including OAuth flows, service principals, scoped tokens, and secret rotation.
  • Build finance-related automations to withstand audits through version-controlled and peer-reviewed changes, automated deployment without manual production edits, least-privilege service identities, preserved segregation of duties, and retained evidence of what ran, when, and under whose authority.
  • Work with Finance and Security Engineering on control design so automation replaces manual controls with stronger automated controls rather than removing them.
  • Apply models for document extraction, classification, or matching when appropriate; use conventional code elsewhere and preserve human decision points required by controls.
  • Build agentic automations for workflows that cannot use a single scripted path; define tools, permitted scope, and blast radius, and ensure human approval before actions affecting money or access.
  • Keep artificial-intelligence use within regulatory boundaries by classifying use cases under the EU AI Act, applying required transparency and human oversight, documenting deployed systems, and escalating employment-decision use cases to Legal before development.
  • Instrument systems so failures surface promptly and run state is visible without reading logs.
  • Maintain deployed automations, including adapting them when upstream application programming interfaces change.
  • Establish patterns, repositories, and review practices that keep internal automation maintainable and auditable as it grows.
  • Challenge processes that should be simplified or removed instead of automated.

Desired Qualifications

  • Experience delivering artificial intelligence systems under the EU AI Act, including risk classification, technical documentation, transparency, and human-oversight obligations.
  • Experience building or operating systems within Sarbanes-Oxley scope, including information technology general controls, change management, segregation of duties, and producing evidence for external audit.
  • Finance systems experience in accounts payable, expense management, bank reconciliation, or enterprise resource planning integration.
  • Experience with Microsoft Graph, Slack, Atlassian, or identity-platform application programming interfaces beyond tutorial level.
  • Experience working under ISO 27001 or SOC 2.
  • Experience with workflow orchestration tools and their failure modes.
  • Production-quality document processing and information extraction experience.
  • Experience in a company scaling beyond 100 people with new processes and evolving requirements.

About the Company

Volta

Financed AI data centers and infrastructure

Volta builds and runs dedicated AI data centres called AI factories and offers AI compute as a financed utility, so labs and enterprises can access Nvidia-class capacity without paying full upfront. It combines capital, land, hardware, software, and day-to-day operations into a single offering, with customers paying for access under multi-year capacity contracts. Unlike traditional data centres, Volta finances and operates the infrastructure and software management to deliver ready-to-use capacity as a service. Its goal is to democratize access to large-scale AI compute across North America and Europe by creating a financed, utility-style infrastructure layer.

Company size
51-200
Company stage
Debt Financing
Total funding
$5.3B
Headquarters
London, United Kingdom
Founded
2026

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