Java Architect/ Lead with AI

Job Title: Java Architect with AI Location:New York, NY Job Type: C2C or W2 Experience: 10+ years (including 2+ years in AI/ML) Industry: IT / Software Development / AI Solutions

Job Summary:
We are seeking a highly skilled and experienced Java Architect with a strong background in AI/ML to lead the design and development of scalable, high-performance applications. The ideal candidate will combine deep expertise in Java technologies with practical experience integrating AI/ML models into enterprise-grade software solutions.

Key Responsibilities:
Lead the architecture, design, and implementation of Java-based microservices and distributed systems.
Integrate AI/ML components into Java applications using APIs, SDKs, or model deployment platforms.
Collaborate with data scientists, DevOps, and software engineers to productionize machine learning models.
Evaluate and select appropriate AI frameworks, cloud services (e.g., AWS SageMaker, Azure ML), and tools.
Ensure best practices in software architecture, scalability, security, and performance tuning.
Guide code reviews, enforce standards, and mentor junior developers and engineers.
Participate in architectural planning, technology selection, and proof-of-concept development.
Design APIs for model serving, including REST, gRPC, and message queues (e.g., Kafka).
Contribute to the development of MLOps pipelines and model lifecycle management.

Required Skills and Qualifications:
10+ years of hands-on experience with Java/J2EE, Spring Boot, Hibernate, and related frameworks.
Proven experience designing and implementing microservices architecture.
Experience working with AI/ML models building, training, or integrating.
Proficiency in consuming AI/ML services via REST APIs, Python microservices, or cloud-based solutions.
Familiarity with machine learning concepts, model evaluation, and deployment strategies.
Experience with containerization technologies such as Docker and Kubernetes.
Good understanding of cloud platforms like AWS, Google Cloud Platform, or Azure, especially their AI services.
Familiarity with MLOps tools (e.g., MLflow, Kubeflow, Airflow).
Solid understanding of data pipelines, ETL processes, and NoSQL/SQL databases.
Strong analytical, communication, and leadership skills.

Preferred Qualifications:
Master's degree in Computer Science, Engineering, or a related field.
Certifications in AWS/Google Cloud Platform/Azure or AI/ML specializations.
Experience with Apache Kafka, Redis, Elasticsearch, or Cassandra.
Exposure to NLP, computer vision, or generative AI is a plus.
Contributions to open-source AI/ML or Java frameworks.