Full Stack AI Engineer (Remote from Houston or Austin TX)

The Friedkin Group•Houston, TX

33d•Hybrid

About The Position

The Full Stack AI Engineer designs and builds enterprise-grade applications that operationalize analytical models, machine learning models, and generative AI solutions. The work spans ingestion pipelines and backend APIs through front-end applications and AI-powered features. The engineer is the primary builder in cross-functional project pods with product owners, enterprise data engineers, and data scientists, and works across data engineering, software engineering, AI engineering, and AI science. The role integrates data pipelines, ML models through APIs, and data serving on Databricks, while using AI coding tools to accelerate delivery and iteration without sacrificing quality. The role includes designing end-to-end solutions across frontend, backend, and data layers; translating analytical outputs and model results into useful business-facing experiences; and building user-facing applications, APIs, workflows, dashboards, data applications, and self-service analytics tools. It also involves developing ingestion and ETL workflows, integrating with Databricks Lakehouse and other data sources, building RAG pipelines and agent memory synchronization, and connecting applications to feature stores, workflows, and ML endpoints. The engineer integrates agentic workflows, RAG pipelines, and AI agents into production applications, and builds features such as semantic search, document understanding, conversational interfaces, and automated workflows. The role also covers CI/CD, testing, observability, monitoring, reliability, documentation, security, and engineering standards. The position is open to in-office and remote work in Houston or Austin, Texas. Remote associates located more than 50 miles from an office are expected to work in-office at least four days per month; this may vary based on project meetings and events. Travel is listed at 20%–30%. Applicants must be authorized to work in the United States without current or future employer sponsorship.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
At least 8 years of experience building production-grade software applications.
Strong full-stack development experience across frontend and backend.
Experience building RESTful APIs and backend services.
Experience with data-intensive applications or data platform integrations.
Experience actively using AI coding tools such as Claude Code, Codex, or Augment Code as part of day-to-day development.
Experience with front-end frameworks such as React, Angular, or Next.
Strong collaboration and communication skills across product, data science, and business stakeholder teams.
Ability to work across multiple layers of the stack without deep specialization in a single area.
Ability to work effectively in ambiguous, fast-moving environments with evolving requirements.
Intellectual curiosity and a drive to stay current on AI tooling, frameworks, and best practices.
Strong engineering discipline, including code quality, testing, documentation, and security awareness.
Legally authorized to work in the United States at hire without requiring employer sponsorship now or in the future.

Nice To Haves

Experience working in agile or scrum delivery models with cross-functional teams.
Experience integrating LLMs, RAG pipelines, or AI APIs into production applications.
Experience with Databricks or Lakehouse architectures.
Experience with cloud-native web application development and deployment on AWS or Azure.
Experience with CI/CD, infrastructure as code, or cloud-native deployments; AWS is preferred.
End-to-end ownership mindset, taking accountability for a product's full lifecycle from pipeline to UI.
AI-native engineering fluency, using AI coding tools effectively as a multiplier.
Product thinking focused on usable, valuable solutions to business problems.

Responsibilities

Design end-to-end solutions spanning frontend, backend, and data layers, and define patterns for scalable AI-enabled applications.
Contribute to architecture decisions and participate in technical reviews across the data and AI ecosystem.
Translate analytical outputs and model results into user experiences that business stakeholders can act on.
Design and build user-facing applications, web apps, APIs, and workflows that enable interaction with data science and AI models.
Build dashboards, data applications, and self-serve analytics tools using modern front-end frameworks.
Develop full-stack solutions using frameworks such as React or Angular and Python-based backends such as Django, FastAPI, or Flask.
Ensure solutions are scalable, secure, and enterprise-ready.
Build and maintain data ingestion pipelines, ETL workflows, and integrations with the Databricks Lakehouse platform.
Build RAG pipelines and data pipelines to synchronize agent memory systems.
Connect applications to data sources, feature stores, workflows, and ML model endpoints.
Ensure data quality, reliability, and performance across pipelines.
Integrate agentic workflows, RAG pipelines, and AI agents into production applications.
Build and deploy AI-powered features, including semantic search, document understanding, conversational interfaces, and automated workflows.
Evaluate and select AI tools and APIs for use cases.
Actively use AI coding tools such as Claude Code, Codex, and Augment Code in development workflows; stay current on tooling and share best practices.
Maintain code quality when using AI-generated code.
Implement CI/CD pipelines, automated testing, and observability for production systems.
Contribute to software engineering best practices for code review, documentation, testing, and security.
Ensure application observability, monitoring, and reliability.
Take accountability for the full product lifecycle, from pipeline to user interface, and collaborate across product, data science, and business stakeholder teams.