Senior Full-Stack Engineer AI Native
# Senior Full-Stack Engineer AI Native **BNamericas** · Remote · `Remote` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Get on Board (LATAM)* --- ### About the Role - 8+ years building and operating production web applications end to end, backend-weighted, with a track record of owning systems rather than tickets. - Strong Python in production. FastAPI is what we use; Django, Flask or similar is fine if you can move across. - Solid relational data modelling and migrations against live data. - Real frontend experience, and the ability to ship usable UI without a design team. Whichever framework you come from, what matters is that you work comfortably on both sides of the line. - Hands-on experience getting LLM-backed systems into production: agent or graph orchestration, RAG, prompt and context design, and evaluating model output rather than trusting it. - Fluent daily use of Claude Code or an equivalent agentic coding tool, with a clear view of where it helps and where it doesn't. - Production experience on a major cloud. We are on AWS: containers, background jobs, secrets, logs, and debugging things that only break in prod. - Autonomy. You'll get context and a goal, not a decomposed backlog. - Documentation creation that let someone else pick the work up. - Professional English - Connection during LATAM (Chile) Business hours STACK: Layer Technologies Backend Python, FastAPI, SQLAlchemy, PostgreSQL (incl. JSONB), schema migrations Frontend Server-rendered Python templates, lightweight JavaScript, Tailwind CSS AI / agents LangGraph multi-agent pipeline, Gemini and Claude, grounded search (serper.dev), Jina extraction, Pinecone for PDF RAG, vision-model OCR Infra AWS: ECS services and tasks, S3, Secrets Manager, CloudWatch, RDS. Docker, Terraform Ways of working Claude Code as a daily tool, Git branch flow, Jira Behind BNamericas is an internal platform that continuously collects data from hundreds of public and private sources, routes it to our research team for verification, and moves it through to publication. We are rebuilding that platform with AI at its core. You'll own features end to end, from schema to interface, and help turn knowledge held by a few people into a system the whole team can carry. Small team, no ticket factory, and real internal users on what you ship within days. Product and platform - Forms and validation: rich, API-integrated data entry for structured content, and the validation rules that keep ittrustworthy. - Workflow: task assignment, draft to review to publish state machines, and admin tooling that lets the businesschange the rules without a deploy. - Dashboards and reporting: progress, throughput, and quality visibility for team leads and leadership. - APIs and integrations: the services connecting this platform to the rest of our systems. - Auth and access control: roles and permissions across an internal product used by several teams. - The data layer: schema design, migrations against live data, and keeping queries fast as volume grows. AI systems - Multi-agent extraction pipelines: agent graphs that collect, extract and reconcile data from public sources atscale, including retrieval, prompt and context design, model selection, rate limiting and cost. - Human-in-the-loop review tooling: interfaces where a reviewer sees what the AI proposed, the alternatives itrejected, the evidence behind each, and can override the machine with a justification that gets recorded and kept. - Audit and provenance: append-only decision trails, so every value can be traced back to a source and to whoeveraccepted it. - Data-quality gating: the checks between what a model produces and what reaches a customer, so nothing AI originated lands unchecked. - Source onboarding: new collectors and per-source parsers, the business rules that go with them, and the admin tooling behind them. - Large-scale scraping or data-extraction pipelines, including third-party scraping platforms. - Data reconciliation, data quality, or human-in-the-loop review tooling. - Infrastructure as code. - Data-heavy B2B products: market intelligence, research or finance. - Mobile app development, particularly an app you built with Claude or similar AI tooling carrying a real part of the work. - Spanish or Portuguese at Intermediate Level
Наблюдалась 2026-10-06, впервые 2026-10-06, источник — Get on Board (LATAM).