Senior Full Stack Engineer

This range is provided by Lead Stack Inc.. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$65.00/hr - $75.00/hr

Direct message the job poster from Lead Stack Inc.

Job Title:

Senior Full Stack Engineer (W2 only)

Location:

Cincinnati, OH (Preferred) — Remote OK within CST/EST Time Zones

Duration: 6+ Months

Rate: $65-$75/hr on W2

We’re seeking a Full Stack Engineer to join our AI Enablement team, responsible for building a data-driven web platform that reports on usage metrics of AI capabilities. The ideal candidate brings strength in front-end (Angular/Type Script), backend (FastAPI/Python), and data pipeline work in Databricks, all hosted in Azure Cloud (AKS).

You’ll collaborate with data scientists, product managers, and designers, driving full-stack initiatives from conception to production. This role is best suited for someone who can handle vague requirements, iterate quickly, and operate with a high level of independence.

• Angular / Type Script
• FastAPI / Python
• Adaptability to vague requirements and fast iteration

• Develop dynamic front-end solutions with Angular/Type Script.
• Build FastAPI-based microservices and integrate RESTful APIs.
• Work with Databricks for data pipelines and schema design (Unity Catalog, Jobs, CLI, environment promotion).
• Participate fully in the software development life cycle (SDLC)—design, develop, test, deploy, and support.
• Operate in the Azure ecosystem, with focus on AKS and Databricks.
• Implement CI/CD automation, testing, and monitoring scripts.
• Collaborate cross-functionally and ensure engineering best practices are met.

• 5+ years of full-stack software development experience.
• Expert in Angular, Type Script, FastAPI, and Python.
• Experience with Databricks, including Unity Catalog, Databricks Jobs, and CLI.
• Cloud experience with Azure (AKS preferred).
• Familiarity with Postgre
  
  SQL, Docker, Kubernetes, and Helm.
• Strong communication and problem-solving skills.
• Ability to work through ambiguous requirements and deliver rapidly.

• Exposure to AI/ML projects or data visualization tools.
• Understanding of data pipelines, quality assurance, and Dev Ops principles.
• Interest in cloud automation and performance optimization.

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