Forward‑Deployed AI Engineer (LLM/ML) — Investigations & Decisioning
Salário Estimado
R$ 12.870,00 - R$ 19.305,00
Descrição da Vaga
At Silent Eight, we develop our own AI-based products to combat financial crimes that enable things like money laundering, the financing of terrorism, and systemic corruption.
We’re a leading RegTech firm working with large international financial institutions such as Standard Chartered Bank and HSBC.
Join us and help make the world a safer place! We solve hard, real‑world problems — from uncovering financial crime, fraud patterns and mule networks, through prioritising thousands of alerts, to crafting defendable case narratives.
We work close to users (analysts, investigators, risk/compliance), iterate fast, and deliver in weeks, not quarters.
The adversary adapts — this is an intelligence game, not an academic benchmark.
The Role We’re looking for someone who solves business problems with technology.
Less stack worship, more outcomes: fast risk identification, fewer false positives, faster time‑to‑decision, better explainability, and lower cost per case.
Finance shows up often, but we think broader — investigations, decisions and client value across industries.
What you’ll do • Go to the field: talk to users, shadow their workflows, capture the as‑is → goals & constraints.
Minimum Requirements • A track record of delivery: 2–3 examples where your AI/ML solution materially improved process KPIs (any industry).
Nice to Have • Experience with investigations / trust & safety / fraud / risk / audit or other complex decision processes.
Our Tech (lightweight) We don’t fetishise the stack.
Common tools: Python, SQL, notebooks/analysis tools, lightweight APIs (e.g., FastAPI), simple stores (e.g., Postgres), and vector indexes.
We choose tools pragmatically — business impact beats heavy infrastructure Note: we don’t expect mastery of “every” tool.
What matters are strong fundamentals, curiosity, and a habit of delivering measurable outcomes.
How We Work A small, seasoned squad.
Weekly goals and regular weekly iterations, a build → measure → learn rhythm.
Minimum ceremony, maximum user contact.
Decisions are captured briefly — in ADRs, tickets, or short notes.
What We Offer • Real influence on decisions in matters that actually count.
Requisitos
- Less stack worship, more outcomes: fast risk identification, fewer false positives, faster time‑to‑decision, better explainability, and lower cost per case
- A track record of delivery: 2–3 examples where your AI/ML solution materially improved process KPIs (any industry)
- Problem‑solving & communication: you can break down fuzzy problems and explain risks to non‑technical stakeholders
- LLMs + ML in practice: RAG, prompting, tool‑calling; classification/ranking/deduplication; fundamentals of evaluation & experimentation
- Python + SQL sufficient to build a prototype that works and can be maintained
- Polish & English fluency for user conversations and concise write‑ups
- Experience with investigations / trust & safety / fraud / risk / audit or other complex decision processes
- Graphs/ER: entity resolution, link analysis, pattern‑of‑life
- Light engineering craft: FastAPI, Docker; the rest (K8s/CI/CD/Terraform) is not required
- What matters are strong fundamentals, curiosity, and a habit of delivering measurable outcomes
- Minimum ceremony, maximum user contact
Responsabilidades
- We’re looking for someone who solves business problems with technology
- Go to the field: talk to users, shadow their workflows, capture the as‑is → goals & constraints
- Define hypotheses & KPIs (precision/recall, FPR, TAT, coverage, cost/decision) and turn them into experiment plans
- Design decision flows that mix LLMs, retrieval/RAG, classical ML, and lightweight rules; ensure explainability and auditability
- Build quick prototypes (notebook → lightweight service/API) and measure their impact on real data
- Create evaluation sets and scoring rubrics (offline + side‑by‑side + sanity checks + guardrails)
- Present findings & recommendations directly to decision‑makers; propose rollout (pilot → production‑lite → scale)
- Lead innovation processes across the company; test, promote solutions and mentor others with new AI technologies
- Weekly goals and regular weekly iterations, a build → measure → learn rhythm
Benefícios
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