Java + AI Engineer (W2 Contract)

Note:

Open only for W2 Contract

The client requires an in-person interview. Candidates must be available to attend the interview at the client’s Sunnyvale/Austin office.

Location:

Austin, TX 78753 / Sunnyvale, CA 94085

Top 3 Required skills:
Java (Spring Boot, Microservices)
GenAI, LLMs, AI/ML frameworks
Python

• Years of experience in each of the must-have skills: At least 8 to 10 years.

About the Role
We are looking for a passionate Java + AI Engineer who can design, build, and integrate intelligent systems into scalable enterprise applications. The ideal candidate has a strong Java development background combined with hands-on experience using AI/ML tools, APIs, and frameworks.

You’ll work closely with cross-functional teams to design robust backend services and embed AI-driven capabilities such as natural language processing, recommendation systems, predictive analytics, and automation.

Key Responsibilities
Design and develop high-performance applications using Java (Spring Boot, Microservices).
Integrate AI models (e.g., via REST APIs, Python services, or cloud AI platforms).
Collaborate with data scientists to deploy and optimize ML models in production.
Build APIs and microservices that enable intelligent data-driven features.
Implement data pipelines for AI workloads, ensuring scalability and reliability.
Evaluate and experiment with GenAI, LLMs, and AI APIs (OpenAI, AWS Bedrock, Vertex AI, Azure OpenAI).
Maintain coding standards, CI/CD pipelines, and cloud deployment best practices (AWS, Google Cloud Platform, or Azure).
Troubleshoot performance issues and ensure application reliability.

Required Skills & Experience
Strong Java development experience (Java 8+, Spring Boot, REST APIs).
Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Hands-on experience or exposure to Generative AI technologies (e.g., LLM integration, prompt engineering, or AI model APIs)
Experience integrating AI APIs (e.g., OpenAI, Hugging Face, Google Vertex AI).
Solid understanding of data structures, algorithms, and software design patterns.
Familiarity with Python for ML model interaction or API wrapping.
Experience with Docker, Kubernetes, and cloud environments (AWS/Google Cloud Platform/Azure).
Knowledge of SQL/NoSQL databases and data ingestion pipelines.
Excellent communication and problem-solving skills.

Preferred Qualifications
Experience working with Generative AI / LLM applications.
Exposure to LangChain, RAG architecture, or vector databases (Pinecone, FAISS).
Understanding of the machine learning lifecycle (training, testing, deployment).
Experience with event-driven systems (Kafka, RabbitMQ).
Contribution to AI-based open-source projects or hackathons.