Senior GenAI Full-Stack Engineer - Brazil
Primary stack
Nice to have's
Job description
About the Position
We are seeking a Senior GenAI Full-Stack Engineer with extensive experience in building and operating production LLM-powered systems to join our team in Brazil.
Responsibilities
- Design and extend production-grade LLM applications and agentic workflows using NestJS, XState v5, and the OpenAI SDK.
- Build and maintain the conversation-machine substrate: guard/action registries, flow validation (ajv), DB-driven flow configs, and design-time tooling.
- Build and evolve the AI systems behind Support Assistant, the player-facing support chatbot, and Agent Support Assistant, the AI copilot used by 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.
- 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.
- Instrument and tune model quality using Langfuse (tracing, evals, prompt management), evaluation datasets, A/B testing, prompt versioning, and production telemetry.
- Manage async workloads via BullMQ and caching with Redis; PostgreSQL persistence via Kysely.
Requirements
Must-Have
- Proven experience building and operating production LLM-powered systems similar in scope to chatbots, AI assistants, agent copilots, RAG systems, or LLM orchestration platforms.
- 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.
- Fullstack depth: comfortable moving between NestJS APIs, React UIs, databases, infrastructure, and production operations.
- Ability to evaluate tradeoffs between model quality, latency, reliability, throughput, and cost.
- Ability to troubleshoot AI systems across prompts, retrieval pipelines, model 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
- Hands-on experience with MCP (Model Context Protocol) or building tool-use agentic workflows.
- Familiarity with Langfuse or other LLM observability/evaluation platforms.
- Experience operating AI workloads at scale.
- Experience evaluating multiple foundation models and providers.
- 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, streaming).
- Previous work in gaming or high-volume consumer products.
We Offer
- Competitive salary
- Full-time employment
- Opportunity to work in Brazil
About the Company
At Codurance, we are committed to building and operating cutting-edge AI systems that drive innovation and improve user experiences. Join our team to make a significant impact in the field of generative AI.
© Codurance. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
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