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- Newton Research
- Junior Software Engineer (Backend + AI)
Junior Software Engineer (Backend + AI)
$90K - $110K/yr
AI Infrastructure
About the Role
Newton Research is hiring a Junior Software Engineer (Backend + AI) for our AI-powered research and analysis platform used by enterprises to unlock insights from their data.
Position: Permanent, Full-time, Junior
Format: Hybrid (Greater Boston Area)
Compensation: $90,000 - $110,000
What you'll do:
- Build Django REST Framework API endpoints with complex data modeling.
- Extend AI agent capabilities — Add new tools to our LangGraph-based agents. Understand how retrieval-augmented generation works by working on our memory system.
- Write async task workers for document parsing and LLM inference.
- Implement comprehensive test coverage with pytest fixtures and API mocking.
- Build React components with TypeScript.
- Diagnose and fix AI output issues ("debug AI output").
You'll work on AI agent pipelines that call LLMs, execute tools, and reason over enterprise data.
Tech Stack:
- Backend: Python 3.13, Django 5.2, Django REST Framework, PostgreSQL, Redis
- AI/ML & Orchestration: OpenAI, Anthropic, and Google LLM APIs; LangChain + LangGraph agent orchestration; sentence-transformers for vector embeddings; RAGAS evaluation
- Data Science: NumPy, Pandas, Polars, scikit-learn, XGBoost, PyMC, Prophet, Plotly
- Frontend: React 19, TypeScript, Vite, Ant Design, TanStack Query, SCSS Modules
- Infrastructure: Docker, GitHub Actions, AWS (S3, ECR), MinIO, Sentry, RQ (Redis Queue)
- Testing: pytest (4,700+ tests), Vitest, Playwright E2E
Required Qualifications:
- Solid Python fundamentals and debugging ability.
- Web API knowledge (HTTP, JSON, request/response cycles).
- Git proficiency.
- Database experience (SQL, schema design).
- Genuine curiosity about AI/ML — you've used LLM APIs, built a RAG pipeline, fine-tuned a model.
- Ability to debug AI-generated code.
Nice-to-Have Skills:
- Django or Flask experience.
- React/TypeScript exposure.
- Docker familiarity.
- Vector databases, embeddings, LLM orchestration frameworks.
- Open-source contributions.
- Deployed projects.
Application Requirements:
- GitHub or portfolio (deployed project, open-source, or documented experiment).
- A note on what you've built with AI tools (emphasis on building, not just using).
- Resume.
Visa sponsorship may be available — application form asks about future sponsorship needs.