Software Engineer, Cloud & Agentic ApplicationsWe have an immediate opening for a hands-on
Software Engineer to help build, extend, and operate cloud-based applications and automation tooling that support NASA customers. You will work alongside senior engineers, architects, and NASA stakeholders to turn defined requirements into working software - writing code, building data pipelines, standing up cloud infrastructure, and iterating based on feedback from users and teammates.
This is a delivery-focused engineering role, not a strategy or advisory position. You will spend most of your time in the codebase: implementing features, fixing bugs, writing tests, deploying to the cloud, and collaborating on architecture decisions that senior staff have already scoped.
Key Responsibilities- Build and maintain backend services and APIs in Python (e.g., FastAPI) and/or TypeScript (e.g., Node/Express), following existing patterns and conventions in the codebase.
- Contribute end to end to internal dashboards and tools - usage/cost analytics and similar applications - implementing features across the API, database, and UI layers.
- Write and maintain data pipelines that ingest, transform, and load structured data (spreadsheet exports, API responses, log data) into PostgreSQL, including schema design and reasonably efficient queries.
- Implement and extend agent-based workflows using frameworks such as Pydantic AI or LangChain - defining tools, prompts, and structured outputs under the guidance of senior engineers, rather than designing agent architecture from scratch.
- Deploy and operate applications in AWS (including AWS GovCloud) using containers, and read and make guided changes to existing Terraform/OpenTofu modules that provision supporting infrastructure such as object storage, managed databases, and container clusters.
- Write unit and integration tests, and keep test suites and CI checks (lint, build, test) passing as a normal part of shipping code, not an afterthought.
- Debug production issues using logs, traces, and database queries, and implement fixes with appropriate test coverage.
- Participate actively in code review - both giving and receiving feedback - as a way of learning the codebase and improving the quality of the team's work.
- Document your changes (README updates, code comments, short design notes) so teammates can pick up where you left off.
- Pair with senior engineers and architects to learn NASA-specific constraints - security, compliance, and approved platforms - and ask questions early rather than guessing.
Requirements- Bachelor's degree in computer science, engineering, or a related technical field, or equivalent practical experience.
- 3-5 years of professional software engineering experience, with solid fundamentals in at least one of Python or TypeScript/JavaScript.
- Working knowledge of cloud computing concepts and at least some hands-on experience with a major cloud provider (AWS preferred) - for example, deploying an application, VPC networking, working with a managed database, using object storage, or writing basic infrastructure-as-code.
- Comfortable working with relational databases (PostgreSQL preferred): writing queries, understanding schema design, and reasoning about basic performance.
- Experience with, or strong interest in, agentic or LLM application frameworks such as Pydantic AI or LangChain - production experience is not required, but you should be comfortable picking up one of these frameworks quickly and enjoy working with LLM-backed tooling.
- Experience with Git-based version control, code-review workflows, and automated testing (unit and integration tests).
- Ability to take a defined task or user story and implement it independently, asking clarifying questions when requirements are ambiguous.
- Clear written and verbal communication with teammates, including the ability to document your own work.
- S. citizenship or other status required to support applicable NASA contracts and access requirements.
Preferred Qualifications- 1+ year of hands-on experience with an agentic or LLM application framework such as Pydantic AI, LangChain, or a comparable tool.
- Experience with Docker and container-based deployment.
- Exposure to Infrastructure-as-Code (Terraform or OpenTofu) - reading and modifying existing modules.
- Experience with FastAPI, Express/Node.js, React, or a comparable modern web framework.
- Familiarity with vector databases, embeddings, or retrieval-augmented generation (RAG) concepts.
- Experience working with or supporting a federal, aerospace, or other regulated environment.
- Interest in data engineering: ETL scripting, pandas, or similar tabular data-processing tools.
- Familiarity with CI/CD pipelines and DevOps practices (linting, build/test gates, automated).
