Full-Stack AI Application Engineer

Ontrac Solutions LLC.; Northern (KY); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Ontrac Solutions LLC. seeks a seasoned Full-Stack AI Application Engineer to own features end-to-end—from data model to user interface—for a contractor program supporting a critical customer engagement.

You will build Python services and a React frontend on Google Cloud, using Vertex AI and Gemini models, and collaborate with the delivery lead and stakeholders to drive delivery from definition to final release.

Qualifications

• 8+ years of professional software engineering experience.
• Experience designing, building, deploying apps on Google Cloud.
• Google Cloud Professional certification (e.g., Professional Cloud Developer).
• Degree in Computer Science or related field, or equivalent practical experience.

Responsibilities

• Build and maintain Python/FastAPI backend services and PostgreSQL data models.
• Develop agent and multi-agent workflows with Vertex AI, Gemini models, and ADK.
• Create React/TypeScript frontend to surface capabilities to users.
• Package and deploy services to Cloud Run and manage data in Cloud Storage.
• Write and maintain automated tests with pytest to ensure delivery stability.
• Collaborate with delivery lead, PM, and customer stakeholders to refine requirements and demonstrate progress.

Skills

Python FastAPI

SQLAlchemy PostgreSQL

Vertex AI Gemini SDK

Agent Development Kit

React TypeScript

Cloud Run Cloud Storage

pytest

Education

BS in CS

Job description

Ontrac is seeking a highly skilled and experienced Full-Stack AI Application Engineer to join a contractor program supporting a critical customer engagement. This role is ideal for a full-stack engineer who can own a feature end to end, from data model through user interface, and who has built and shipped applications on Google Cloud using Vertex AI and the Gemini models. The successful candidate should be equally comfortable writing Python services and React front ends, should be able to work from loosely defined requirements without heavy oversight, and will work closely with the delivery lead, the Program Manager, and customer stakeholders to ensure project success from initial definition through final delivery.

ENGAGEMENT

• Location: United States only, fully remote

REQUIRED CREDENTIALS

• 8 or more years of professional software engineering experience
• Demonstrated experience designing, building, and deploying applications on Google Cloud Platform
• Google Cloud Professional certification, for example Professional Cloud Developer or Professional Machine Learning Engineer
• A degree in Computer Science or a related field, or equivalent practical experience

REQUIRED QUALIFICATIONS

• Strong Python (3.11 and later), with production experience building REST APIs, ideally with FastAPI
• Relational data modelling with SQLAlchemy and PostgreSQL
• Hands-on experience with Vertex AI and the Gemini models through the google-genai SDK
• Experience building agent and multi-agent workflows, ideally with Google's Agent Development Kit (ADK)
• Front-end development with React 18 and TypeScript
• Experience packaging and deploying containerized services to Cloud Run, and working with Cloud Storage
• Comfortable writing and maintaining automated tests with pytest

USEFUL QUALIFICATIONS

• Retrieval and grounding with Vertex AI Search
• Familiarity with the wider front-end toolchain: Vite, Tailwind, TanStack Query, and Zustand
• End-to-end testing with Playwright
• Local development with Docker Compose, and comfort with the gcloud CLI and pnpm
• Prior delivery experience with a Google Cloud partner
• Experience working directly with customer stakeholders in a consulting or delivery setting

SCOPE AND DELIVERY EXPECTATIONS

The following covers the scope of work we anticipate the contractor supporting throughout the project. This scope is in line with our expectations of the project but is subject to change.

• Build and maintain the Python and FastAPI backend services, along with their PostgreSQL data models, that underpin the application
• Implement agent and multi-agent workflows using Vertex AI, the Gemini models, and ADK, including retrieval and grounding through Vertex AI Search where the solution calls for it
• Develop the React and TypeScript front end that surfaces these capabilities to end users
• Package and deploy services to Cloud Run and manage application data and artifacts in Cloud Storage
• Write and maintain automated tests, using pytest and Playwright, to keep delivery stable as the application grows
• Take part in working sessions with the delivery team and customer stakeholders to refine requirements, resolve technical questions, and demonstrate progress
• Produce the technical documentation needed to support handover at the close of the engagement