Agentic Coder

About TradeifyTradeify is a next-generation proprietary trading firm that funds futures traders — giving skilled traders access to real capital without the red tape. We offer evaluation-based and instant funding paths, letting traders choose the route that fits their style and get to profitable trading faster. We're building the infrastructure, tooling, and intelligence layer that sits behind that experience: real-time dashboards, automated journaling, risk management systems, and AI-powered workflows that help traders grow their accounts and our team operate at scale. We move fast, think in systems, and care deeply about the traders who trust us with their careers. About the RoleWe're not looking for someone who "has experience with AI." We're looking for someone who builds with it every day — an engineer whose default instinct is to reach for an LLM, an agent framework, or a durable workflow instead of writing another for-loop. This is a high-ownership, high-output role. You'll design and ship agentic systems that touch real users and real money. You'll work alongside a product team that moves fast and expects the same. If your idea of a good week is shipping an internal tool on Monday, wiring up a RAG pipeline on Wednesday, and deploying a Discord bot by Friday — read on. What You'll Build • Multi-step AI agents that handle complex, real-world workflows end to end • RAG pipelines that actually perform — not just LangChain defaults • Durable background workflows for processing, enrichment, and orchestration • Internal dashboards, admin tools, and integration surfaces (Slack, Discord, Intercom) • Eval harnesses to measure and improve model performance over time • The glue layer between LLMs, APIs, databases, and product features What We're Looking ForLanguages & Foundations • Python 3.12 as your primary language — you live in the AI/ML ecosystem; FastAPI for AI/agent service APIs • TypeScript (strict) in a monorepo on Bun + Turborepo — Next.js (App Router), React, Tailwind, shadcn/ui for UI; Hono + tRPC for the API layer; Better Auth for authentication • Comfortable with SQL and Drizzle ORM with PostgreSQL — comfortable querying and working with a relational data modelLLM & Agent Tooling • Hands-on with Anthropic, OpenAI, and Google Vertex AI (Gemini) APIs — function/tool calling, structured outputs, prompt caching; multi-provider failover via OpenRouter and Cloudflare AI Gateway • Production experience with an agent framework: LangGraph for agent/AI services — not just a weekend project • Familiar with Model Context Protocol (MCP) — building and consuming MCP clients/servers to extend agent capabilities • You know the boring-but-critical stuff: streaming, retries, token cost management, rate limitingRAG & Retrieval • Experience with vector DBs: pgvector (preferred), Pinecone, Weaviate, or Qdrant • Intentional about embedding models and chunking strategy — you've reasoned about trade-offs, not just accepted defaults • Implemented hybrid search (BM25 + vector) when precision mattersOrchestration & Workflows • Code-first workflow experience: BullMQ + Redis for queues, scheduled jobs, and durable background orchestration • Aware of low-code tools: n8n, Zapier, Make — can use them when appropriate • Background jobs, queues, and scheduled tasks are second natureEvals & Observability • Active user of at least one eval/observability platform: Langfuse (self-hosted) for tracing and evals — our primary observability platform; familiarity with LangSmith, Braintrust, or Helicone is a plus • You've actually run an eval set — you have opinions on what makes a good oneAI-Native Dev Workflow • Claude Code is your daily driver — plus comfort operating within a homegrown agentic-dev layer (hooks, skills, subagents) • You ship internal tools in days, not sprints • You have a "vibe coding" instinct — but you don't let it erode eng disciplineInfrastructure • Comfortable deploying on AWS (EC2, S3, SES, ECR, Parameter Store) in us-east-2; Docker / Docker Compose for dev and prod; Caddy for TLS and reverse proxy; GitHub Actions + OIDC for CI/CD • Docker / Docker Compose, env management, and secrets handling (AWS Parameter Store) are table stakes • Some Biome, Vitest, and Playwright familiarity is a plus for linting, unit testing, and end-to-end testingProduct Glue • Can spin up Next.js (App Router) / React dashboards and admin interfaces when needed • Familiar with Discord.js, Slack API, and Intercom API; comfortable with Asana, Fellow, and Google Workspace (Drive/Calendar/Gmail) integrations • Understands product instrumentation with Mixpanel or GA4 Bonus Points • You've built LLM-powered side projects that real people actually use • You understand trading or trading platforms — this accelerates your empathy with our users enormously • You have genuine opinions on model selection (Claude vs. GPT vs. open-weight) — you don't treat them as interchangeable black boxes What You Won't Find Here • Bureaucracy slowing down good idea