Senior GenAI Full-Stack Engineer - Brazil

Codurance

Responsibilities

\- Build and evolve the AI systems behind Epic Support Assistant (ESA), the
player-facing support chatbot, and Agent Support Assistant, the AI copilot used by
\- Instrument and tune model quality using Langfuse (tracing, evals, prompt

\- Proven experience building and operating production LLM-powered systems
similar in scope to chatbots, AI assistants, agent copilots, RAG systems, or LLM
\- Strong TypeScript/Node.js engineering; TypeScript strict-mode fluency
\- Production AI experience: prompt engineering, RAG pipelines, agent design, tool
calling, model evaluation, observability, and failure-mode analysis — you've shipped AI

\- Fullstack depth: comfortable moving between NestJS APIs, React UIs, databases,
infrastructure, and production operations; you don't artificially limit yourself to one layer
\- Ability to evaluate tradeoffs between model quality, latency, reliability, throughput,
configuration, infrastructure, and application code
\- State machine thinking — you naturally model complex async workflows; XState or
similar experience is a strong signal
\- Solid understanding of REST API design, async patterns (queues, events), and caching
strategies
\- Strong testing culture: unit, integration, and contract tests are first-class deliverables, not
afterthoughts
\- Experience working in a monorepo with multiple interconnected services
Strong Plus

Codurance · Brazil (Remote) · Full-time · Posted 2026-10-06

Design and extend production-grade LLM applications and agentic workflows using
NestJS, XState v5, and the OpenAI SDK — flows include RAG, intent detection,
clarification, fulfillment, escalation, tool-use, and human-in-the-loop state machines
\- Build and maintain the conversation-machine substrate: guard/action registries, flow validation (ajv), DB-driven flow configs, and design-time tooling in Epicenter admin customer support agents
\- Integrate with MCP servers (Model Context Protocol) for tool-use and agentic behaviors
\- Evaluate, benchmark, and tune models across providers including OpenAI, Gemini,
Anthropic, and future providers; own model selection decisions balancing quality,

\- Troubleshoot production LLM issues including hallucinations, retrieval failures, prompt regressions, model drift, token inefficiencies, latency bottlenecks, and provider outages
\- Build resilience mechanisms: retries, fallback routing, caching, streaming, rate limiting,
and provider routing management), evaluation datasets, A/B testing, prompt versioning, and production telemetry
\- Manage async workloads via BullMQ and caching with Redis; PostgreSQL persistence via Kysely

\- Ability to troubleshoot AI systems across prompts, retrieval pipelines, model
\- Hands-on experience with MCP (Model Context Protocol) or building tool-use agentic workflows
\- Familiarity with Langfuse or other LLM observability/evaluation platforms

\- Experience building AI copilots, assistants, or conversational products
\- Experience with semantic search and retrieval architectures
\- Experience with AI gateways such as Portkey or similar platforms
\- Experience with NestJS specifically: modules, providers, guards, interceptors, DI patterns
\- Background in customer support or player support platforms — you understand the stakes of getting AI-generated responses wrong
\- Experience shipping under low-latency constraints (chatbot response time budgets,

\- Previous work in gaming or high-volume consumer products

[Apply at Codurance](https://apply.workable.com/codurance/j/82BC037A3B/apply)