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The AI Developer Engineer will be responsible for designing, developing, and deploying scalable applications using Python or Java. The ideal candidate should have strong programming skills and hands-on experience with AI/LLM platforms, particularly in the banking domain. The role requires collaboration with cross-functional teams and a good understanding of cloud platforms, especially GCP. A bachelor’s or master’s degree in Computer Science, Engineering, or a related field is required, along with 4–8 years of experience in software development.
Job Responsibility:
Design, develop, and deploy scalable applications using Python or Java
Build responsive and modern user interfaces using React.js
Develop data pipelines using modern toolsets on public cloud platform
Develop AI-powered solutions using LLM technologies such as Vertex AI, Gemini, or similar platforms
Implement Retrieval-Augmented Generation (RAG) architectures and work with vector databases, embeddings, and semantic search
Integrate AI capabilities into enterprise applications and APIs
Work with cloud platforms (GCP preferred) for deployment, scaling, and monitoring applications
Collaborate with cross-functional teams including data engineers, architects, and product teams
Ensure best practices for code quality, security, and performance optimization
Requirements:
4–8 years of experience in software development & data workflow development
Strong programming skills in Python and/or Java and SQL
Hands-on experience with React.js for front-end development
Good understanding of Data Lake, Data Pipeline, ETL/ELT
Experience with Generative AI / LLM technologies (Vertex AI, Gemini, OpenAI, or similar)
Good understanding of RAG frameworks, embeddings, vector databases, and prompt engineering
Experience working with public cloud platforms (GCP preferred, AWS/Azure acceptable)
Knowledge of API development and microservices architecture
Nice to have:
Experience with Relational Databases (RDBMS)
Exposure to Kubernetes / containerized deployments
Familiarity with CI/CD pipelines and DevOps practices
Experience working in AI-driven or data-intensive applications