Top Python Jobs in Austin, TX

Develop, design, and deliver complex Python backend applications for acquiring, storing, and computing on large volumes of data. Lead feature implementation, ensure code quality via linting and automated tests, mentor junior developers, perform code reviews, collaborate with cross-functional teams, and troubleshoot production issues.

Develop and maintain scalable Python backend applications and RESTful APIs. Optimize performance, design and manage SQL/NoSQL schemas, implement security/authentication, write tests, automate CI/CD tasks, and collaborate with front-end, product, and QA teams.

The Senior Python Engineer will develop and support MongoDB Python drivers, enhance library quality, and collaborate on product features.

Develop and maintain Python applications focusing on iterators/generators/streams, concurrency (multithreading, non-blocking I/O), and high-precision numeric handling. Work with JSON/XML, REST and SOAP APIs, ACID-compliant databases, message brokers/queues, and produce clean, SOLID code. Unit and integration testing experience is beneficial.

Work as a Python development intern building applications and APIs, processing and analyzing data, working with databases and data pipelines, contributing to system architecture, writing clean documented code, and collaborating with the team. Strong emphasis on backend development, SQL, ORMs, and REST API design with potential conversion to full-time.

Concept Plus seeks a Junior Python Developer to enhance enterprise-scale applications, focusing on backend development, DevSecOps practices, and secure coding under senior guidance.

Seeking an expert Python developer with 10 years of experience to design solutions, lead teams, and optimize legacy frameworks. Experience in Google Cloud and Flask/Web2Py is required.

Lead projects and coordinate engineering teams, focusing on scalable backend systems, improving processes, and ensuring alignment with business goals.

Design, develop, and maintain scalable Python applications and cloud-native solutions. Architect microservices, containerized deployments (Docker/Kubernetes), optimize cloud infrastructure, build CI/CD pipelines, integrate messaging systems, ensure security and high code quality, and mentor junior developers. Generative AI/ML experience is a plus.

The Staff Software Engineer coordinates engineers' activities, determines technical tasks, improves processes, and collaborates with management to meet objectives.

The Senior Software Engineer will deliver software solutions throughout all phases of the SDLC, advise management, guide junior engineers, and make technical decisions with minimal supervision.

The Senior Full Stack Developer will design, develop, test, and debug software solutions, collaborating with teams and optimizing applications. Responsibilities include user interaction design, back-end functionality, and ensuring software scalability and security.

The Principal Python Engineer will design, build, and maintain backend services and APIs, focusing on system reliability and engineering quality. The role involves working with databases, applying DevOps practices, and leveraging AI for development efficiency.

The Python Engineer will write maintainable Python software, lead technical initiatives, collaborate globally, and contribute to community engagement at Canonical.

Design, develop, and maintain scalable Python applications; collaborate with cross-functional teams to deliver features; ensure performance and quality; identify and fix bugs; maintain code quality and automation; lead and mentor team members using agile practices.

Join the Trading Engine team to develop and maintain client-facing open-source libraries, act as an SME for REST and WebSocket trading APIs, and work directly with large clients to design and optimize trading algorithms and integrations.

Develop Python microservices and APIs using FastAPI. Implement data validation with Pydantic and enforce linting (flake8). Integrate pyMongo with MongoDB collections, connect services to GraphQL endpoints and graph databases, and configure and maintain Neo4j database instances.

Develop Python microservices and APIs using FastAPI; implement data validation with Pydantic; enforce linting (flake8); integrate with MongoDB via PyMongo; connect to GraphQL and graph databases; install and configure Neo4j.

Design, build, test, and maintain backend applications using FastAPI and SQLAlchemy. Implement database schemas, integrate front-end components, optimize for performance and scalability, debug issues, participate in code reviews, and collaborate on feature design. Maintain clean, testable code and stay current with best practices.

Design, develop, and maintain scalable microservices and RESTful APIs using Python (FastAPI) and Node.js. Collaborate with cross-functional teams across the full SDLC, write testable code, troubleshoot and improve system performance, and contribute to architectural and process improvements.

Own end-to-end product features for a SaaS platform serving HR, therapists, and employees. Build, scale, and evolve frontend and backend components, lead architecture and standards, collaborate with design and product, and incorporate customer feedback and QA. Work in an early-stage startup environment with product-focused ownership.

The Senior API Engineer is responsible for designing, building, and operating cloud-native REST APIs using Python on AWS, focusing on security, performance, and infrastructure management with Terraform and CI/CD practices.

Nagarro seeks an Associate Principal Engineer with extensive IT experience in Python to drive strategic value and innovation in product engineering.

Design and implement durable, fault-tolerant AI orchestration and backend systems using Temporal and agentic ReAct patterns. Deliver features end-to-end with testing, CI/CD, monitoring, and observability; mentor engineers and collaborate with cross-functional teams to translate legal workflows into reliable AI-powered features.

Design and build backend systems and APIs for AI-driven products, ensuring scalability, reliability, and integration of ML models while collaborating with engineering and product teams.