Developer II - Python

Neuberger Berman•New York, NY

1d•Hybrid

About The Position

Neuberger is looking for a curious and motivated Junior Python Developer to join their growing engineering team. This role involves building reliable, scalable server-side applications in a modern, AI-augmented development environment, leveraging cutting-edge tools to work smarter, ship cleaner code, and grow fast. The ideal candidate is comfortable writing clean Python, has hands-on experience with containerized workflows, and is genuinely excited about the future of AI-assisted development.

Requirements

Python: 3+ years of hands-on experience
Frameworks: Proficiency in Flask, FastAPI, or Django
AI Tools: Working experience with GitHub Copilot, Claude, or comparable LLM-based coding assistants
LLM Awareness: Understanding of tokens, context, prompting, limitations, and responsible use
Containers: Hands-on Docker experience — build, run, and debug containerized applications
Version Control: Proficient with Git (branching, PRs, rebasing)
Testing: Ability to write meaningful unit tests; familiarity with pytest or similar
ORM: Working knowledge of SQLAlchemy, Django ORM, or equivalent

Nice To Haves

Familiarity with Kubernetes, OpenShift, or container orchestration concepts
Exposure to cloud platforms (Azure, AWS, or GCP)
Experience calling or integrating LLM APIs (OpenAI, Anthropic, Azure OpenAI)
Understanding of RAG patterns or vector stores
Basic front-end literacy: JavaScript, HTML5, CSS3
Familiarity with server-side templating (e.g., Jinja2)
Understanding of async or multi-process architecture (asyncio, multiprocessing)

Responsibilities

Build and implement server-side features, modules, and components in Python following clean code and best practice standards
Collaborate with product and design teams to translate business requirements into well-structured, maintainable code
Participate in code reviews — giving and receiving constructive feedback
Use AI coding assistants (GitHub Copilot, Claude, etc.) responsibly to accelerate development, improve code quality, and reduce repetitive boilerplate
Apply a working understanding of LLMs — tokenization, context windows, prompt construction, and model limitations — to integrate them sensibly
Identify the right use cases for AI tooling vs. traditional logic, and flag risks like hallucinated outputs or sensitive data exposure
Write and maintain Dockerfiles and work within containerized development environments
Apply core container concepts: images, containers, volumes, networking, and basic orchestration (Docker Compose, Kubernetes/OpenShift)
Contribute to deployable, environment-consistent application packaging
Participate in sprint planning, stand-ups, retrospectives, and reviews
Break down user stories into actionable tasks and deliver working software within sprint timelines
Maintain transparency with the team on progress, blockers, and dependencies
Write and maintain unit and integration tests to ensure reliability and regression safety
Debug and resolve defects from testing or production monitoring
Collaborate with QA to develop test cases and uphold software quality