Senior Software Engineer (AI & Python) - 61916816384

• Build and integrate LLM-powered features into the product, from prototyping through production.
• Develop NLP and retrieval pipelines using LangChain, vector databases, and the broader Python AI ecosystem (Pandas, NumPy, and similar).
• Design and reason about multi-agent systems, anticipating how small changes ripple through a probabilistic, AI-first system.
• Translate research-style approaches into reliable, maintainable production systems.

• Make heavy, daily use of AI in your own engineering workflow — we provide top-tier tooling (e.g., Claude Max 20x, ChatGPT Pro 20x).
• Regularly use and contribute to our internal skills, agent integrations, and agentic loops, raising the quality of their outputs across our software development, testing, and documentation use cases.

• Work with vector databases to power retrieval and AI-driven features.
• Store and manage data in NoSQL/document databases (e.g., MongoDB or similar).
• Make sound decisions about data structure, performance, and scalability.

• Design, build, and consume GraphQL and REST APIs.
• Contribute to a microservices-oriented architecture within a monorepo environment.

• Maintain a high bar for code quality through detailed peer review.
• Own testing across unit, integration, and end-to-end layers.
• Work within CI/CD pipelines and contribute to keeping them healthy.
• Document your work clearly using markdown and inline comments so others can build on it.

• 5+ years of professional software engineering experience. Many strong candidates for this role will have 10+ years; we weigh demonstrated competence over years.
• Expert-level proficiency in Python. This is the primary language of the role and is non-negotiable.
• A genuine foundation in AI beyond the surface level — you can explain how inference works and reason from first principles, so you can logic through how small changes affect behavior in an AI-first system. Critical to the work.
• Intimate knowledge of vectors and vector databases. Critical to the work.
• Hands-on experience designing or working with multi-agent systems. Critical to the work.
• Practical, hands-on experience building with LLMs, including LangChain and the supporting Python AI ecosystem (Pandas, NumPy, and similar). Critical to the work.
• Daily, fluent use of AI in your own workflow, plus the habit of improving it — regularly using and contributing to internal skills, agent integrations, and agentic loops.
• Experience with NoSQL/document databases (MongoDB or similar).
• Comfort designing and consuming both GraphQL and REST APIs.
• Proficiency with Git. Non-negotiable — it is the de facto standard for how we work.
• Familiarity across modern development practices: detailed peer review, unit/integration/end-to-end testing, microservices, monorepos, and CI/CD pipelines.
• Strong written communication and a genuine willingness to document processes thoroughly.
• Ability to maintain at least 75% daily overlap with U.S. Eastern Time.

• Familiarity with Go (Golang). Not required — a nice-to-have for occasional tasks alongside Python.
• Exposure to security, developer tooling, or AI agent / coding-agent products.
• Prior experience as an early or foundational engineer at a startup.

You are:

• Highly competent and self-directed — you can take an ambiguous problem and drive it to a production solution without close supervision.
• Comfortable in an early-stage environment — you move quickly, make pragmatic tradeoffs, and are energized by building foundational systems rather than maintaining mature ones.
• A clear communicator and strong documenter — you leave behind work others can understand and extend.
• Rigorous by instinct — testing, peer review, and clean data design are how you naturally operate, not chores.
• AI-native — you already work AI-first, have informed opinions about how to get the best out of frontier models and agents, and stay close to how the field is moving.