Full Stack Software Engineer - AI

blueStone Solutions Group; Austin (TX); Hybrid; USD 83,000 - 124,000; Full time

Job summary

blueStone Solutions Group in Austin, TX is seeking a Full Stack Software Engineer (AI Focus) on a contract-hybrid basis. You will own end-to-end development of scalable Java backends and React frontends, integrating cutting-edge AI frameworks and LLMs into production systems.

Lead architectural decisions, balance latency and cost, and leverage AI tooling like LangChain, LlamaIndex, and Vector Databases to deliver robust dashboards and internal tools.

Qualifications

• Backend experience in Java and microservices architecture.
• Frontend architecture ownership and React UI delivery.
• Hands-on AI/ML stack experience with LangChain, LlamaIndex, HuggingFace.
• Experience with vector databases and AI integration (RAG, agents).
• Strong system design and end-to-end solution expertise.
• Proficient in prompt engineering and AI validation.

Responsibilities

• End-to-End Engineering: architect, build, deploy full-stack solutions.
• Backend Development: scalable APIs, microservices, batch systems.
• Frontend Development: dashboards and internal tools with React.
• AI & LLM Integration: AI-powered features into production environments.
• Model Management: evaluate and integrate AI models; optimize latency and cost.
• Modern Workflows: use AI-assisted tools to improve code quality and velocity.

Skills

Java

Microservices

Backend Architecture

React

System Design

Prompt Engineering

LangChain

LlamaIndex

HuggingFace

Vector Databases

Tools

Cursor

GitHub Copilot

Claude Code

Job description

Job Title: Full Stack Software Engineer (AI Focus)

Job Type: Contract- Austin Texas Hybrid

No immigration related sponsorship will be provided for this role. Please do not apply for this role if you require employer sponsorship. This includes direct company sponsorship or entry of an employer as the immigration employer of record or any work authorization requiring written immigration support from an employer. All candidates need to be legally eligible to work in the United States.

About the Role

We are seeking an innovative Full Stack Software Engineer with specialized expertise in Artificial Intelligence to drive the development of our next-generation applications. In this role, you will own the end-to-end lifecycle of new features, building highly scalable Java backends and dynamic React frontends while integrating cutting-edge LLMs and AI frameworks.

You will be expected to make critical architectural decisions, balance model trade-offs (cost, latency, accuracy), and leverage AI-assisted tooling to accelerate development.

Key Responsibilities

• End-to-End Engineering: Architect, build, and deploy robust full-stack solutions, designing everything from the data model and API structure to the user interface flow.
• Backend Development: Build scalable APIs, microservices, and batch-processing systems utilizing Java.
• Frontend Development: Own and develop intuitive, responsive UIs for dashboards, internal tools, and public-facing applications using React.
• AI & LLM Integration: Design and implement AI-powered features (e.g., RAG systems, AI agents, chatbots, recommendation engines) into production environments.
• Model Management: Evaluate, select, and integrate appropriate AI models (OpenAI, Anthropic Claude, Gemini, Llama) and handle optimization for latency, accuracy, and operational cost.
• Modern Workflows: Utilize modern AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude Code) to improve code quality, validate outputs, and enhance engineering velocity.

Required Skills & Qualifications

• Backend Expertise: Strong professional experience in Java ecosystem architecture and microservices development.
• Frontend Expertise: Proven track record of owning frontend architecture and delivering complex UIs in React.
• AI/ML Frameworks: Hands-on experience with the modern AI stack, including LangChain, LlamaIndex, Hugging Face, and Vector Databases.
• System Design: Exceptional ability to conceptualize new services from the ground up, making sound architectural choices across the entire stack.
• Problem Solving: Demonstrated ability to navigate the unique technical challenges of AI implementation, including prompt engineering, context window limits, and output validation.