AI Engineer

• Develop and enhance AI-powered applications using LLMs, RAG frameworks, and modern AI services.
• Build and integrate APIs, AI workflows, and automation solutions under the guidance of senior team members.
• Support implementation of AI use cases using GitHub Copilot, Claude, Azure AI Services, OpenAI models, and Databricks.
• Participate in evaluating and testing new AI tools and technologies.
• Assist in developing prompt engineering and retrieval-based solutions for business applications.

Software Engineering

• Design, develop, test, and maintain high-quality software applications and services.
• Contribute to all phases of the Software Development Lifecycle (SDLC), including development, testing, deployment, and production support.
• Follow engineering best practices for code quality, security, performance, and maintainability.
• Develop REST APIs, microservices, and cloud-native applications.
• Participate in code reviews and continuously improve development practices.

Data & AI Engineering

• Support development of data pipelines and AI-ready datasets using Databricks, Spark, SQL, and related technologies.
• Assist in implementing vector search, embeddings, and retrieval solutions for AI applications.
• Monitor and troubleshoot AI application performance, reliability, and operational issues.
• Analyze data and model outputs to improve solution effectiveness and user experience.

Collaboration & Delivery

• Work closely with product managers, business stakeholders, data engineers, and senior developers to deliver AI solutions.
• Participate in Agile ceremonies, sprint planning, backlog refinement, and team discussions.
• Document technical designs, implementation approaches, and operational procedures.
• Communicate progress, risks, and challenges effectively within the team.

Security & Responsible AI

• Follow Mastercard security, privacy, and Responsible AI guidelines during solution development.
• Support testing and validation of AI solutions for accuracy, reliability, and compliance.
• Participate in risk assessments and quality reviews as required.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
• 3-5 years of software engineering experience.
• Experience with one or more programming languages such as Java, Python, or JavaScript.
• Understanding of software development fundamentals, APIs, databases, data structures, and cloud technologies.
• Exposure to AI/ML concepts, Generative AI, LLMs, or machine learning solutions.
• Experience with Git, CI/CD pipelines, and Agile development methodologies.
• Strong analytical, problem-solving, and communication skills.