AI & Data Scale: Work directly with LLM pipelines, agent orchestration, and statistical systems to process massive streams of organic data.
Drive Standards: Improve system reliability, performance, observability, and maintainability across our cloud infrastructure.
Collaborate & Lead: Work cross-functionally to clarify product requirements, evaluate technical trade-offs, and make pragmatic architecture decisions.
Leverage Modern Workflows: Thoughtfully utilize AI tools to accelerate development velocity, elevate code quality, and optimize internal loops.
Qualifications
Experience: 5–8 years of professional software engineering experience building production-grade software.
Core Stack: Strong backend development experience with languages such as Python, Ruby GO, Java or similar.
Workflow Orchestration: Experience building, scheduling, and monitoring pipelines using Astro / Apache Airflow, Langchain etc.
Distributed Systems: Practical understanding of distributed systems architecture, microservices, and message queues/event streaming (e.g., Celery, Redis, RabbitMQ, or Kafka).
System Design: Strong foundation in computer science fundamentals, software architecture, performance optimization, and scalable data-intensive systems.
Nice to have
Education: Degree in Computer Science, a related technical field, or equivalent deep practical experience.
Frontend Familiarity: Experience with React and TypeScript is highly valued.
Data & Databases: Hands-on experience working with document databases (e.g., MongoDB) and handling analytical data formats like Parquet.
Cloud Infrastructure: Familiarity with deploying and monitoring applications in cloud environments (Azure preferred)
Ideal Candidate
Comfort with ambiguity: You can take a vague “this workflow is painful” and turn it into a concrete diagnosis, a clear path forward, and working software.
Strong ownership: You proactively identify what needs doing, drive solutions forward, and close loops without waiting for every detail to be defined.
Bias for shipping: You make pragmatic decisions, balance quality with speed, and know when to iterate.
Strategic mindset: You understand the “why” behind your work and can explain technical trade-offs to technical and non-technical stakeholders.
Deep curiosity: You read the docs, ask good questions, and learn new domains because you want to understand how things work—not just what you need to ship.
AI-first mindset: You actively use AI tools to improve your development workflow and are excited to keep experimenting with new ways to build software.
