The Role

We are helping to hire a Senior Software Engineer to strengthen the core foundation of our agentic data analytics platform, ensuring reliability, scalability, and performance as we move from MVP to enterprise scale.

This is a core platform role with real ownership. You will work on data integrations, platform execution, and the systems that power AI-driven analytics.

What You Will Be Doing

• Building core data integrations with common SaaS platforms
• Designing data pipelines that ingest provider APIs into our analytics datastore
• Improving the agent platform and executor with better error handling, observability, and speed
• Making LLM interactions more efficient through prompts, snippets, and tooling
• Improving internal developer experience and platform tooling
• Helping take an early MVP into a production-grade platform

Why Join

• Early, high-impact role in an AI-native company
• Direct influence on platform architecture and technical direction
• Opportunity to work with an experienced founding team
• Build technology that fundamentally changes how teams use data

The Stack

• Go (Railway)
• Postgres
• Terraform (Infrastructure as Code)

What We Are Looking For

• 3+ years of Go experience
• Deep understanding of design patterns and system architecture
• Experience building scalable, performant platforms
• Strong grasp of event-driven systems and concurrency
• Solid database and API design experience, ideally with Postgres
• Understanding of good security practices
• Ability to clearly communicate technical trade-offs
• Familiarity with the modern AI tooling landscape
• Some cloud infrastructure experience including Terraform

Nice to Have

• Zero-to-one product experience, including OSS or side projects
• Data engineering experience such as pipelines and analytics
• Experience integrating LLMs, including prompt design and understanding model capabilities
• Deeper cloud experience, especially with GCP
• Experience with Encore, though this is easy to pick up

Ways of Working

• Ownership mindset with comfort taking ideas from rough outline to implementation
• Execution first approach where speed matters, balanced with pragmatism
• Iterative development focused on shipping, learning, and improving
• First-principles thinking rather than cargo-cult engineering
• Ego-less culture with direct, constructive feedback
• Comfort working asynchronously and learning independently
• AI-native approach using tools like Cursor or Claude Code to move faster