AI Application Engineer

Role & responsibilities

• Design, develop, and deploy end-to-end AI and machine learning applications.
• Build robust OCR and Document Intelligence pipelines tailored for financial data extraction and processing.
• Architect and implement advanced solutions utilizing Agentic AI frameworks and RAG (Retrieval-Augmented Generation).
• Use Python extensively for data processing, model building, and workflow automation.
• Apply statistical and ML techniques to solve real-world use cases like predictive modeling, fraud detection, and customer analytics.
• Deploy, monitor, and ensure the scalability of models in cloud environments (AWS / Oracle Cloud).
• Collaborate cross-functionally with business, data, and engineering teams to deliver AI-driven business solutions.

Preferred candidate profile

• Experience: 2 to 5 years of hands-on engineering experience in AI/ML or Data Science roles.
• Domain Knowledge: Strong understanding and previous project experience in the Finance, Banking, Risk, or FinTech domains.
• Core Tech Stack: High proficiency in Python, Machine Learning algorithms, Deep Learning, NLP, and Generative AI.
• Specialized Skills: Proven expertise in building scalable OCR solutions, Agentic AI, and RAG architectures.
• Bonus Skills: Hands-on experience with Django, REST APIs, SQL/MySQL, and Cloud AI Services.
• Availability: Must have a maximum notice period of 20 days (Immediate joiners are highly preferred).
• Work Setup: Must be a proactive self-starter comfortable working in a permanently remote environment.