What are the responsibilities and job description for the Lead Java AI Engineer position at Veridian Tech Solutions, Inc.?
Hi,
Hope you are doing good!
We have a Full-time opportunity for you as Lead Java AI Engineer @ Austin, TX
Role: Lead Java AI Engineer
Locations: Austin, TX
Type of Hiring: FTE
Client is seeking a passionate Lead 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, and exposure to Generative AI and LLMs.
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 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, OpenAI).
- Maintain coding standards, CI/CD pipelines, and cloud deployment best practices (AWS, GCP).
- Troubleshoot performance issues and ensure application reliability.
Required Qualifications:
- At least 4 years of experience in Information Technology.
- Experience in Java/J2EE development
Preferred Qualifications:
- At least 3 years of experience in Java/J2EE development
- At least 3 years of experience in DB SQL/NoSQL.
- Strong knowledge of Spring Boot, Microservices, Spring Security, Spring MVC, Spring Data, JPA, Hibernate.
- Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn).
- Experience integrating AI APIs (OpenAI, Hugging Face, Google Vertex AI).
- Hands-on experience designing and integrating microservices using REST APIs and asynchronous messaging (Kafka).
- High-level knowledge of CI/CD.
- Familiarity with Generative AI technologies (LLM integration, prompt engineering, AI model APIs).
- 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/GCP/Azure).
- Exposure to LangChain, LangGraph, 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.
- Strong analytical and troubleshooting skills.
- Excellent oral and written communication skills.
- Ability to independently learn new technologies.
- Passionate, team player, and fast learner.