What are the responsibilities and job description for the Lead Java AI Engineer position at Avance Consulting?
Job Title : Lead Java AI Engineer
Location : Austin, Texas ( On Site )
Job Type : Full-time
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 7 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.