You will work on determining how to best incorporate large language models (LLMs) and other AI technologies into our product. You will collaborate closely with our Product and Design teams to explore the boundaries of what’s possible with AI, find innovative ways to apply these capabilities to Financial Planning & Analysis (FP&A), and ship features with a meaningful impact on our users’ workflows.
What You’ll Be Doing:
● Work hand-in-hand with leadership and cross-functional teammates to prioritize and execute on our product roadmap.
● Own the end-to-end development of new AI features, from rapid prototyping to full implementation in our core product.
● Deliver robust, scalable, and thoroughly tested code.
● Help define and establish best practices that lay the foundation for a high-performing engineering team and culture.
● Collaborate with Design and Operations teams.
Core Competencies:
AI & Engineering Skills:
● Experience in software engineering; AI Engineers with solid software engineering foundations are preferred.
● Strong understanding of LLMs, RAG systems, Agents, and Multi-Agent architectures.
● Experience with systems such as DeepResearch, Text2SQL, or Chat with Data (they are actively building new features).
● Tech stack: Python, Google ADK (nice to have), FastAPI, Tabular (nice to have), Ruff.
● Knowledge of AI agent frameworks.
● Testing experience using pytest.
Data & Databases:
● Experience with relational and non-relational databases.
● BigQuery, PostgreSQL, and PGVector.
● MongoDB.
● Strong data-handling skills: querying data warehouses, performing operations such as pivoting, drill up/down, etc.
Architecture & Distributed Systems:
● Experience designing scalable and resilient solutions (monoliths, microservices, micro frontends).
● Frontend modularization: monorepos, Storybook, UI as a composable system.
Production, CI/CD & Cloud:
● Experience with CI/CD pipelines (GitHub Actions).
● GCP + containers.
● Monitoring tools: Datadog, Langfuse.
Soft Skills:
● Exceptional clarity when explaining technical concepts — this is a must.
● Real seniority and maturity — must be able to demonstrate this through experience and communication.
● Proven impact and ownership in previous projects.
● Strong critical thinking — must be able to challenge decisions and propose alternatives.
● Ability to work in real-world, high-ambiguity scenarios.
● Autonomy and proactivity — startup environment mentality.
● Data/Finance experience is a nice to have.
Language Requirements:
● Strong conversational English.
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