What are the responsibilities and job description for the Full Stack AI Application Developer position at OakTree Staffing?
Full Stack AI Application Developer
Location: Houston, Tx
Description:
Seeking a Full Stack AI Application Developer to design, build, and scale enterprise-grade artificial intelligence applications that support critical Refining and Midstream business initiatives. In this role, you will work on highly visible AI solutions that move beyond experimentation into production, partnering closely with internal technical leaders to deliver Generative AI applications that drive real operational and financial impact.
They will be responsible for end-to-end application development, including front-end user interfaces, middle-tier services, back-end APIs, databases, and cloud infrastructure. This role requires hands on experience implementing Generative AI capabilities such as Retrieval-Augmented Generation (RAG), knowledge graphs, and AI agents, as well as collaborating with cross functional stakeholders to translate business problems into scalable technical solutions.
The ideal candidate is technically strong, adaptable, and comfortable working in a fast-paced enterprise environment where priorities evolve quickly. The organization values practical skill and execution over tenure and offers the opportunity to work on cutting-edge AI initiatives within a company that is actively investing in enterprise AI platforms, data modernization, and digital transformation.
Responsibilities:
- Design, develop, and enhance full stack applications that integrate Generative AI capabilities into business workflows.
- Expand and operationalize Retrieval-Augmented Generation (RAG) models and extend existing knowledge graphs to support scalable analytics and insights.
- Build, configure, and maintain AI agents and agentic workflows that interact with enterprise systems and data sources.
- Develop and manage back-end services, APIs, and cloud-based databases to support AI-driven applications.
- Collaborate closely with internal technical teams to transition AI solutions from prototype or hackathon outputs into production-ready applications.
- Apply AI-assisted development techniques to accelerate delivery while maintaining engineering quality and security standards.
- Adapt quickly to evolving requirements and deliver solutions on aggressive timelines aligned to high-visibility AI initiatives.
Additional Skills & Qualifications
- Oil and gas experience
- Experience working in enterprise-scale environments, particularly with regulated industries such as energy, manufacturing, or industrial operations.
- Familiarity with KQL (Kusto Query Language) and large-scale data querying or analytics platforms.
- Experience integrating AI solutions with enterprise search, document repositories, or collaboration tools such as SharePoint, Teams, or internal knowledge bases.
- Exposure to cloud platforms, especially Microsoft Azure services, including identity, security, and data services.
- Experience supporting high-visibility, fast-paced initiatives, such as hackathons, pilots, or proofs of concept that transition into production.
Employee Value Proposition (EVP):
- This role offers the opportunity to go full-time with a large oil and gas downstream provider in Houston. This role directly supports the organization's enterprise AI strategy and contributes to solutions with meaningful business and operational impact. The contractors selected will help shape how AI applications are built, scaled, and reused across the organization, with opportunities to support additional AI initiatives as momentum continues.
Business Drivers/Customer Impact:
The organization has an abundance of AI use cases that need to be developed. This role addresses the business challenge of transforming high-value AI ideas into scalable, production-ready solutions that improve operational efficiency, reduce costs, and replace expensive third-party systems. By building and expanding Generative AI applications tied to integrity, data, and operational decision-making, the role directly impacts the organization’s ability to make faster, smarter, and more reliable decisions across Refining and Midstream operations. The customer impact is increased reliability, improved margins, and a stronger competitive position through the use of modern, internally owned AI solutions.