Remote AI Agent Engineer

fram^ is looking for the Remote AI Agent Engineer. The core product experience runs on an LLM-driven agent that extracts data from client-submitted receipts and documents over WhatsApp, proposes accounting entries, and answers staff questions inside the web app. We’re hiring an AI/Agent Engineer to take ownership of this entire layer — making it cheaper, safer and more reliable — while closing specific security gaps (prompt injection, unchecked tool authorization) identified in a recent technical audit. You will work alongside a backend-leaning Full-Stack Engineer, who owns the surrounding application and infrastructure.

Responsibilities

• Own the LLM integration layer used for document extraction (OCR), accounting-entry proposals, and the in-app chat agent, currently built on Anthropic/OpenAI APIs
• Implement prompt caching to cut redundant token usage — an identified ~83% cost-reduction opportunity — and introduce per-tenant usage budgets and quotas
• Harden the agent against prompt injection: treat all extracted document text as untrusted input, and require explicit confirmation gates before any tool call that grants data access, creates a contact, or moves money
• Replace the agent’s currently hard-coded (effectively disabled) permission model with real, enforced per-tool authorization checks
• Evaluate and implement model tiering — cheaper models for extraction, stronger models for judgment calls — and plan a fallback provider for resilience
• Build an evaluation / golden-file test harness so model or prompt changes can be validated before shipping to production
• Implement PII redaction before data is sent to third-party LLM providers, and partner with the Full-Stack Engineer to log every agent tool call to an audit trail
• Advise on data-processing-agreement and data-residency questions for the AI sub-processors (Anthropic, OpenAI), alongside the company’s data-protection advisor
• Contribute to the n8n-side automation where it touches AI extraction — the document-intake pipeline — coordinating handoffs with the Full-Stack Engineer.

Qualifications

• 3+ years of experience building production applications on top of LLM APIs (Anthropic Claude, OpenAI, or equivalent)
• Hands-on experience with agentic tool-use patterns — function/tool calling, multi-step agent loops — not just single-shot prompting
• Strong prompt-engineering skills, including context management and techniques for defending against prompt injection
• Proficiency in Python or TypeScript, sufficient to build and modify a backend AI-integration layer
• Experience building or using evaluation frameworks / golden-file testing for LLM-based systems
• Practical understanding of LLM cost structures and optimisation techniques — prompt caching, context trimming, model tiering
• Working knowledge of security concerns specific to LLM systems: prompt injection, data exfiltration via generated content, unsafe tool authorization
• Clear written communication in English; able to work asynchronously across time zones

Nice to have

• Experience with OCR / document-extraction pipelines specifically — receipts, invoices, financial documents
• Familiarity with Swiss accounting concepts (MWST/VAT codes, KMU chart of accounts), or willingness to learn them quickly
• Experience with n8n or a similar workflow-automation tool
• Background in a regulated or compliance-sensitive domain (fintech, healthtech, legal tech)