Software Developer

What You'll Do Build Gen-AI product features - Design and ship agentic workflows that turn author briefs into simulations, roleplays, assessments, and coaching experiences Engineer for production - Write robust TypeScript services and APIs; handle streaming, latency, cost, rate limits, failure modes, and observability for LLM-backed features Develop AI agents - Build and orchestrate multi-step agents (planning, tool use, structured outputs, guardrails) that generate and refine learning content reliably Evaluate and iterate - Build evals and feedback loops to measure generation quality, catch regressions, and improve prompts/agents systematically Collaborate and communicate - Work with product managers, learning designers, and fellow engineers; write clear design docs, articulate trade-offs, and present your work Stay current - Track the fast-moving Gen-AI landscape (models, agent frameworks, retrieval techniques) and bring the best of it into KNOLSKAPE's products What We're Looking For Must-Have 2+ years of professional software engineering experience , with strong proficiency in JavaScript/TypeScript (Node.js on the backend; React or similar on the frontend is a plus) Hands-on Gen-AI experience - you've shipped features built on LLM APIs (Anthropic, OpenAI, Gemini, or similar), not just experimented in notebooks Experience building AI agents - multi-step orchestration, tool/function calling, structured outputs, and handling the messiness of non-deterministic systems Experience with RAG - embeddings, vector databases (pgvector, Pinecone, or similar), chunking strategies, and retrieval quality tuning Strong communication skills - you can explain technical decisions to non-engineers, write clear documentation, and collaborate effectively across teams Product mindset - you care about what authors and learners experience, not just what the model outputs Ownership and self-direction - you can take an ambiguous problem, scope it, and drive it to a shipped outcome Nice-to-Have Experience with agent frameworks (LangChain/LangGraph, Vercel AI SDK, Claude Agent SDK, or hand-rolled orchestration) Experience building LLM evals or quality measurement pipelines Familiarity with prompt engineering at scale — versioning, templating, A/B testing prompts Experience with streaming UX (SSE/WebSockets) for real-time AI interactions Exposure to speech/multi-modal AI (TTS, STT, avatar/video generation) Experience with cloud platforms (AWS, GCP, or Azure), Docker , and CI/CD Background in ed-tech, learning platforms, or other content-generation products