Java AI Engineer

Job Overview:

We are seeking a Senior Full Stack (AI) Engineer to design, develop, and deploy AI-powered applications. The ideal candidate will have expertise in both front-end and back-end development, with a strong focus on integrating AI/ML models into scalable and user-friendly solutions. This role requires a proactive mindset, a passion for innovation, and the ability to collaborate with cross-functional teams to deliver high-impact AI solutions in a fast-paced environment.

Key Responsibilities:

• AI-Powered Application Development: Design, build, and deploy full-stack applications that integrate AI/ML models for predictive analytics, automation, and intelligent decision-making.
• Front-End Development: Develop responsive, dynamic, and user-friendly interfaces using modern JavaScript frameworks such as React.js or Angular.
• Back-End Development: Build robust, scalable, and secure server-side applications using Python, Java, or Node.js.
• AI/ML Integration: Implement and fine-tune AI models, particularly Large Language Models (LLMs), for various business use cases.
• Database Management: Work with both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) to manage structured and unstructured data efficiently.
• DevOps & Cloud Deployment: Deploy, monitor, and optimize applications using AWS, Azure, or Google Cloud with a focus on scalability and performance.
• Security & Compliance: Ensure best practices in data security, access control, and compliance within banking and financial services.
• Collaboration & Agile Development: Work closely with data scientists, product managers, and other engineers to rapidly develop, iterate, and deploy AI-driven solutions.

Required Skills & Experience:

• 7-8 years of experience in full-stack development, with a strong focus on AI integration.
• Expertise in front-end frameworks such as React.js, Angular, or Vue.js.
• Proficiency in back-end technologies like Python (Django/Flask), Java (Spring Boot), or Node.js.
• Strong understanding of AI/ML models, particularly LLMs, NLP, and predictive analytics.
• Experience with DevOps tools (Docker, Kubernetes, CI/CD pipelines).
• Familiarity with cloud platforms (AWS, Azure, GCP) and AI model deployment.
• Experience in banking and financial services is highly preferred.
• Ability to commute to the client's New York office 2 days a week.

Preferred Skills:

• Hands-on experience in LLM engineering and fine-tuning AI models.
• Knowledge of MLOps for managing machine learning workflows in production.
• Understanding of API development and microservices architecture.
• Strong problem-solving and analytical skills with a results-driven mindset.