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Volta is a vertically integrated AI infrastructure platform building compute infrastructure for frontier AI customers. This role removes manual internal work that multiplies as the company scales: invoice retyping, expense report chasing, spreadsheet reconciliation, and manual account provisioning.
You will sit with process owners across finance, IT, People, and delivery to understand workflows and build integrations that run them automatically against banking and accounting systems, Microsoft Graph, Office, Slack, Jira, Confluence, and the HR and identity stack. Most work is well-built API code with sound authentication, error handling, escalation, auditability, and observability. You will apply models for classification, extraction, or matching where they are the right tool rather than fashionable, and use conventional code elsewhere.
Much of this work lands inside the financial reporting path. Volta is building toward SOX compliance alongside ISO 27001 and SOC 2 obligations. Automations touching invoices, payments, or reconciliation become part of the control environment immediately upon going live. You build to that standard from the first commit: changes are reviewed, tested, and traceable; access is least privilege and segregated; every run leaves an audit trail external auditors can follow; and code moves to production through controlled deployment, never by hand.
Regulation shapes the work in a second way. Volta is headquartered in the UK and operates across the EU, so anything you build with AI sits under the EU AI Act as well as UK and EU data protection law. Automations touching hiring, performance, or employment decisions carry the heaviest obligations. You are expected to recognize where the line between a helpful classifier and a regulated decision system runs, keep a person in the loop where the law requires one, document what you deploy, and bring Legal and Security in early.
You sit inside Corporate IT at a fast-growing AI-forward company, which owns the tooling, accounts, and API access you build on and provides engineers next to you for design discussion and code review. Security Engineering advises on access and compliance. Initially you are the only person doing this work full time, so you prioritize hard, ship small, and build things that keep running without you next to them.
Key responsibilities include: automating finance operations (invoice ingestion, classification, matching, exception handling); working directly with process owners to turn described workflows into specified, testable automations; building and running integrations against internal systems; owning authentication and credentials (OAuth flows, service principals, scoped tokens, secret rotation); building finance-touching automations to withstand audit; working with Finance and Security Engineering on control design; applying models where they earn their place and using conventional code elsewhere; building agentic automations with human approval gates before anything with money or access impact; keeping AI use inside regulatory boundaries; instrumenting what you build for immediate failure visibility; maintaining deployed systems; setting patterns and review practices; and pushing back when a process should be simplified or deleted instead of automated.
REQUIREMENTS:
- Production software development held to the standard of an engineering team, not scripting
- Fluency across more than one software ecosystem (Python and Go come up often but neither is required)
- Deep practical work with third-party APIs: pagination, rate limits, idempotency, retries, webhooks, and integration behavior under failure
- Real command of authentication mechanisms: OAuth 2.0, OIDC, service accounts, API key and secret management
- Disciplined engineering practice producing audit trails: source control, code review, automated testing, controlled deployment, separation between build and release
- Hands-on experience building with LLMs, including tool use and structured extraction, plus judgment to recognize when a model is the wrong answer
- Hands-on work with agentic patterns: tool and function calling, MCP or equivalent tool interfaces, state and retry handling across multi-step runs, testing agent behavior
- Working awareness of rules governing AI and automated decision-making in workplace context
- Ability to sit with subject matter experts, understand business processes, and implement them correctly
- Track record of building reliable, secure, auditable systems rather than demos
- Comfort as the only engineer on a problem: choosing what to build next and owning the outcome
NICE TO HAVE:
- Delivering AI systems under the EU AI Act: risk classification, technical documentation, transparency and human oversight obligations
- Building or operating systems in SOX scope: IT general controls, change management, segregation of duties, audit evidence
- Finance systems experience: accounts payable, expense management, bank reconciliation, ERP integration
- Microsoft Graph, Slack, Atlassian, or identity platform APIs at more than tutorial level
- Work under ISO 27001 or SOC 2
- Workflow orchestration tooling and failure modes
- Document processing and information extraction at production quality
- Experience at a company scaling past 100 people with new processes and moving requirements
