Loại hình
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Kỹ thuật / Cơ khí
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Thương lượng
Địa điểm
Quận 1, Hồ Chí Minh, Hồ Chí Minh
Tổng quan
- 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 Fullstack 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 and coordinating handoffs with the Fullstack Engineer.
- Your Skills and Experience
- 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
- Why You'll Love Working Here
- You’ll love working here!
Quyền lợi
- Be a developer, not a coder
- Excellent environment and team to help you grow.
- The Job
- 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…
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