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Senior Full Stack (AI) Engineer ----

Salary undisclosed

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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, Google Cloud Platform) 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.

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