AI Engineer
4 days ago
We are looking for a Prompt / AI Engineer who combines a builder mindset with experimentation and product thinking. This role is R&D-focused and offers the freedom to explore, prototype, validate, and ship AI-driven solutions that improve productivity and operational efficiency, even when requirements are loosely defined or evolving. The role emphasizes applied AI, ownership, and practical impact over theoretical research.
Responsibilities
- Identify workflow bottlenecks independently and design AI-assisted solutions to address them.
- Prototype, validate, iterate, and ship AI-driven tools from concept to production.
- Improve efficiency across operations, accounting workflows, support, and internal reporting, including initiatives without formal specifications.
- Build AI features that:
- Extract structured insights from unstructured reports and documents
- Detect anomalies and outliers with clear, explainable rationale
- Convert voice or natural language instructions into safe, auditable actions
- Automate repetitive operational tasks while maintaining control and correctness
- Design, refine, and maintain prompts, tool-calling schemas, and structured extraction pipelines that perform reliably in real-world conditions.
- Implement lightweight evaluation and quality checks, including golden datasets, regression testing, and failure-mode tracking.
- Apply guardrails such as validation, safe defaults, fallbacks, and uncertainty handling.
- Own projects end-to-end, including problem discovery, solution design, prototyping, stakeholder feedback, iteration, and delivery.
- Provide pragmatic recommendations on what to build, what not to build, and when solutions are ready to ship.
- Communicate outcomes clearly, including what was tested, what succeeded, what failed, and recommended next steps.
- Collaborate with engineering to integrate AI features via clean service boundaries and dedicated AI endpoints.
- Make architectural decisions related to synchronous vs. asynchronous workflows, background processing, streaming outputs, and retries.
- Support observability through traceability of model calls, cost and latency awareness, and production monitoring.
Skills Needed / Qualifications
Required
- Demonstrated experience delivering projects where AI meaningfully improved workflows.
- Hands-on experience with:
- Automated insights extraction from reports, documents, emails, or spreadsheets
- Anomaly or outlier detection that reduced review effort or prevented errors
- Natural language or voice-driven automations that trigger real-world actions safely
- Strong familiarity with modern AI tools and LLM ecosystems (e.g., ChatGPT, Codex, Claude) and the ability to apply them creatively.
- A builder mindset with proven ability to design, test, and refine practical AI solutions.
Strongly Preferred
- Software engineering background (computer science, backend, full-stack, or systems development).
- Experience integrating AI into production systems and designing APIs or services.
- Exposure to observability and debugging in production environments, including logs, traces, and error analysis.
Nice-to-Have
- Familiarity with FinTech or accounting workflows.
- Experience with speech-to-text or voice-based user experiences.
- Knowledge of privacy and security considerations in AI systems, including PII handling, access controls, and audit logging.
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