Get more replies from employers
Send a job-specific resume in minutes.
TXFront in Seattle, WA is seeking a Python Developer / AI Engineer to design, build, and scale AI-powered applications and cloud-native platforms using Python, AI/ML, LLMs, and Azure.
You will work with data scientists and cloud engineers to deliver scalable APIs and secure, reliable services, employing Docker, AKS, CI/CD, and SAFe practices.
This role offers a full-time, on-site position in Seattle with opportunities to impact enterprise solutions.
Job Title: Python Developer / AI Engineer | TXFront | Seattle, Washington, USA
Recruiting Company: TXFront
Job Location: Seattle, Washington, USA
Job Type: Full-Time
TXFront is seeking an experienced Python Developer / AI Engineer to build and scale next-generation AI-powered applications and cloud-native platforms. This role combines advanced Python software development with Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), and Azure cloud technologies to deliver innovative enterprise solutions.
As a Python Developer / AI Engineer, you will work on the design, development, deployment, and optimization of intelligent applications leveraging modern AI and machine learning technologies. You will collaborate with data scientists, cloud engineers, product teams, and business stakeholders to develop scalable AI-driven products and enterprise services. The role requires strong expertise in Python development, microservices architecture, Azure cloud platforms, container orchestration, and modern DevOps practices. You will contribute to building robust APIs, integrating AI services, deploying cloud-native applications, and optimizing solution performance and security. This is an exciting opportunity to work at the forefront of AI innovation while leveraging cutting-edge cloud and software engineering technologies.
To stand out, showcase projects where you successfully deployed AI or LLM-based solutions into production, highlighting the business impact, Azure cloud architecture, MLOps practices, API integrations, scalability improvements, and measurable outcomes achieved through your engineering and AI expertise.