Jr. Software Engineer (L1)

About this role

About Atlas Data Science Atlas Data Science builds Paxium, a data management and governance platform that gives organizations one metadata hub to discover, access, use, and share many kinds of data. Paxium covers the data lifecycle from receipt, through metadata capture and enrichment, to discovery and dissemination, so that suppliers and consumers of data (including AI agents) can work from governed, well-described data. We are a small team. You will work on real product code next to experienced engineers. The role We are hiring a full-time Junior Software Engineer with up to two years of professional experience. You will build and ship features for Paxium's metadata capture, transformation, and delivery, with an experienced engineer as your mentor, and grow toward owning larger pieces of the product. This role starts immediately. • Level: L1, junior. Up to 2 years of professional experience • Employment: Full-time (one opening) • Location: Hybrid, On-site New York City or Washington DC (1-2 days per week) • Start date: Immediate What you'll do You will work with experienced engineers on a modern stack that includes TypeScript, Python, Java, Postgres, OpenSearch, Kubernetes, Airflow, Terraform, and GitLab. You will start with well-scoped tasks and take on more independence as you grow. You will: • Build, test, and maintain parts of the pipelines that capture, transform, and deliver metadata for Paxium. • Write backend code in Python, and contribute to services in Node.js or Java as the work needs. • Build and consume REST APIs, and work with data in relational databases such as PostgreSQL, including SQL queries and data modeling. • Write unit, integration, and system tests for everything you ship. • Open merge requests in GitLab, take part in code review, and work through CI/CD pipelines. • Run and debug containerized services using logs and operational metrics. • Work with senior engineers and DevOps on infrastructure as code and deployment, learning as you go. • Break a task into smaller pieces and take it from design through completion, with guidance. • Keep learning current tools and practices, including AI-assisted development and how AI systems use metadata. We care more about strong fundamentals and how you learn than about the exact number of years of experience. • A bachelor's degree in computer science or a closely related field, or equivalent hands-on software development experience (internships, freelance, open source, or substantial projects). • Up to two years of professional software development experience. Internships, co-ops, and substantial project work also count. • Solid Python skills, shown through professional work, internships, or hands-on projects beyond coursework, such as a service you built, containerized, and ran. • Working knowledge of SQL and relational databases such as PostgreSQL, plus data structures and algorithms. • A working understanding of REST APIs and backend services. • Familiarity with Docker and running services in containers. • Experience with Git and code review. You can work through a branch, a merge request, and feedback. • A basic understanding of authentication, authorization, and why secrets need careful handling. • Experience debugging with logs and comfort learning to read operational metrics. • Clear written and spoken communication, and a habit of asking questions early. • Comfort working in a small, collaborative team that ships in short cycles. None of these are required. Any of them helps. • Experience with AI-assisted development tools, and good judgment about when to trust their output. • Exposure to a workflow orchestration tool such as Airflow, or asynchronous workflows with retries and timeouts. • Exposure to a search engine such as OpenSearch. • Familiarity with authorization models such as RBAC or ABAC, or a policy engine such as OPA. • Interest in metadata management, data lakes, or lakehouse technologies. • Hands-on experience with LLM-powered applications, such as Retrieval-Augmented Generation, semantic search with embeddings, or AI agents. • Demonstrated interest in AI agents and how they're secured and governed, through a class project, a side project, or reading. For example: • AI agents that connect to real data and tools, such as through MCP or an agent framework • Running AI models on local GPUs or edge hardware instead of the cloud • Security for AI agents, such as identity, permissions, and isolation • Governing which data AI systems can access and use • Experience with TypeScript, Node.js, Java, Kubernetes, or Terraform. • A personal project or open-source contribution we can look at. • US Citizen.

1. Intro to Atlas/ Candidate Q&A: 15 minutes with VP of Finance and Ops and a member of our Engineering team
2. Panel Interview with Technical Leadership: 45 minutes
3. Technical Test: 45 minutes
4. Meet the CEO: 30 minutes