We're looking for a Senior Software Engineer to join the founding team and own the technical backbone of Scope. You'll work directly with the founding team to design, build, and deploy features end-to-end, spanning TypeScript/Node, React/Next.js, Python/FastAPI, and the LLM and agent frameworks that power the Scope Context Layer.
This is a senior IC role for someone who can move from rough idea to production system without hand-holding, and who has the technical judgment to make architecture decisions that hold up as the company scales. You'll be one of the first engineering hires, so you'll have real influence over architecture, systems, and product direction while building the technical backbone of a new generation of AI-driven tools.
This role has a hybrid work arrangement in Buenos Aires, Argentina.
- Lead the design and implementation of core platform features end-to-end across React/Next.js, Node, and Python/FastAPI, with an eye for long-term maintainability and clear reasoning about tradeoffs
- Design APIs and data models that hold up under real usage, integrating with external systems like Slack, Jira, Salesforce, and Drive without creating brittle dependencies
- Own infrastructure and ensure the system behaves predictably under load while keeping security and cost discipline in mind
- Create and operate CI/CD pipelines, monitoring, logging, and alerting that give real visibility and support rapid iteration
- Set the bar for code quality through thorough reviews, clear patterns, and direct mentorship as we scale the team
- Influence architectural choices and challenge assumptions to push the product toward a cleaner, more resilient foundation
- 5+ years building and shipping production systems across both frontend and backend
- Deep proficiency in Python for backend development including API design, async patterns, and performance-minded architecture
- Strong command of TypeScript, React and Next.js including SSR, routing, data fetching models, and state management patterns
- Demonstrated ability to design and operate production infrastructure using Docker and Kubernetes on GCP or AWS plus Terraform and CI/CD pipelines
- Hands-on experience building agentic systems such as task planning, constrained tool use, or multi-agent orchestration in production settings
- Comfort working with LLM frameworks such as LangChain, LangGraph, the Anthropic and OpenAI SDKs, and MCP, with the judgment to know when to use them and when to avoid them
- Ability to reason clearly about system behavior, tradeoffs, and failure modes
- Comfortable working in small teams with high ownership expectations, able to take a feature from rough idea to deployed product without hand-holding
- Hands-on experience with vector databases like Qdrant or Pinecone, including schema design, ingestion pipelines, and tuning for hybrid retrieval
- Practical familiarity with multimodal embedding models and retrieval workflows
- Background in implementing RAG pipelines at scale including chunking strategies, indexing, caching layers, and latency tradeoffs
- Experience with message queues and event-driven systems such as Celery, Pub/Sub, or Kafka to coordinate async workflows used by agents
- Prior experience as a tech lead or staff engineer at an early-stage startup