Lead Python Developer

Quick Facts

• Hybrid: 3 days/week onsite (Schaumburg, IL; locals only)

Description

Lead backend-focused Python development to design, build, test, and maintain Python services, data pipelines, and workflow automation. Collaborate with senior engineers on microservices and API integrations, support SQL/cloud data work and observability, and help integrate backend systems with emerging AI-enabled capabilities.

Role description

You will implement and refine backend logic, write modular automation scripts, build REST API connectivity, and assist with lightweight UI/dashboard integrations for internal testing and demos.

You will also support data engineering and cloud operations by transforming and validating datasets with SQL, deploying and monitoring backend microservices and pipelines in cloud environments, and improving reliability via benchmarking and log/error analysis.

Finally, you will design and maintain automated unit, integration, regression, and performance tests using pytest, curate test data, and contribute to clean architecture, documentation, and continuous improvement.

Responsibilities

• Partner with senior engineers to implement, refine, and debug backend logic, microservices, and API integrations
• Develop modular Python scripts and utilities to automate data ingestion and batch processing workflows
• Build and consume RESTful APIs and integrate with internal tools and third-party services
• Support lightweight frontend/dashboard integrations for testing and demos (e.g., React or Python-based internal UI tools)
• Write efficient SQL queries for dataset extraction, transformation, inspection, and validation
• Support configuration, deployment, and monitoring of microservices and data pipelines in cloud environments
• Monitor application performance, track error rates, inspect service logs, and optimize resource/API usage
• Design and maintain automated test suites (unit, integration, regression, performance) using pytest
• Benchmark API latency, validate system outputs, and verify regression stability
• Curate, sanitize, and manage structured test datasets and mock environments
• Maintain clear documentation (runbooks, API specifications, setup guides, architectural notes)
• Participate in Agile planning, stand-ups, technical brainstorming, and peer code reviews

Requirements

• Bachelor’s or master’s degree in Computer Science, Software Engineering, Data Science, or related field (or equivalent practical experience)
• 2–3+ years of professional, internship, or open-source software engineering experience with strong Python
• Strong Python skills: OOP, asynchronous scripting, pandas/numpy, and software design patterns
• Experience writing and maintaining automated test suites using pytest or unittest
• Proficiency in SQL for relational databases and/or cloud data warehouses (e.g., PostgreSQL, MS SQL Server, MySQL)
• Foundational hands-on experience or familiarity with cloud platforms; Google Cloud preferred (e.g., BigQuery, Cloud Run)
• CI/CD pipeline familiarity and containerization using Docker
• Experience with modern web technologies (e.g., React) and/or Python FastAPI or rapid-prototyping libraries (e.g., Streamlit)
• Basic AI/LLM understanding and ability to work with AI coding tools (e.g., GitHub Copilot)

Preferred Qualifications

• Generative AI principles, prompt engineering, LLM APIs, and agentic concepts (e.g., RAG, embeddings, semantic search, tool use)
• Hands-on familiarity with agentic frameworks and orchestration libraries (LangChain, LangGraph, LlamaIndex, CrewAI, Google Agent Builder/ADK)
• Familiarity with LLM evaluation and validation frameworks (Ragas, DeepEval, Promptfoo, or custom eval harnesses)
• Experience with Model Context Protocol (MCP) and advanced tool/REST API integrations into automated agent workflows
• Exposure to safety and guardrails (synthetic data generation, red-teaming, toxicity filtering, hallucination detection)