Job Title     : AI Solution Engineer  
Experience : 0-5 Years
Location     : INDIA      

Job Description :

• As an AI Solution Engineer you will be responsible for developing, deploying, and

• implementing advanced AI-enabled applications for our highly sophisticated systems, ensuring

• compliance with security standards and delivering innovative and efficient solutions within a

• secured environment. Self-discipline and a strong desire to build applications with high integrity

• are essential for success in this role.

What you will do:

• Research and Innovation: Stay updated with the latest AI technologies, tools, and

• trends to continuously improve and innovate data conversion processes.

• Documentation: Maintain comprehensive documentation of AI solutions,

• methodologies, and deployment processes.

• Design and Develop AI Models: Implement AI solutions focused on automating and

• enhancing the core data conversion processes.

• Data Handling: Work with large datasets, ensuring the integrity and security of sensitive

• information during the conversion process.

• Secure Environment Compliance: Develop and deploy AI solutions in accordance with

• security protocols, ensuring all processes meet compliance standards.

• Collaboration: Work closely with cross-functional teams including data scientists,

• software engineers, and business analysts to create integrated AI solutions.

• Testing and Validation: Conduct rigorous testing and validation of AI models to ensure

• accuracy and reliability.

• Performance Optimization: Continuously monitor and optimize AI models for efficiency

• and performance improvements. Perform application scoring and data aggregation

What you will need to have:

• Programming Skills: Proficiency in programming languages such as Python, JS/NodeJS, and .NET

• Framework/Core C#.

• Machine Learning Frameworks: Familiarity with ML frameworks and libraries such as

• TensorFlow, PyTorch, Keras, or Scikit-Learn. Experience in selecting and implementing

• appropriate algorithms for specific tasks is highly valuable.Data Handling and Processing: Experience with data manipulation and analysis using tools like

• Pandas or NumPy. Understanding how to preprocess data, handle unstructured data, and

• create datasets for training models is crucial.

• Deep Learning: Knowledge of deep learning concepts and architectures, including convolutional

• neural networks (CNNs), recurrent neural networks (RNNs), and transformers, especially for

• tasks related to image recognition, natural language processing, and more.

• Software Development Practices: Familiarity with software development methodologies,

• version control systems (like Git), and DevOps principles to ensure smooth integration and

• deployment of AI models.

• Cloud Computing: Experience with cloud-based services and platforms (e.g., AWS, Google

• Cloud, Azure) that provide tools for machine learning and AI deployment.

• System Design: Ability to design scalable AI systems, including understanding architecture

• patterns, APIs, and microservices for integrating AI models into broader applications.

• Problem-Solving: Strong analytical and problem-solving skills to identify the best AI solutions

• for various challenges and to troubleshoot issues that arise during implementation.

• Collaboration and Communication: Experience in working collaboratively with cross-functional

• teams, including data scientists, software engineers, and business stakeholders, to align AI

• solutions with business objectives.

• Hands-on Experience: 5-7+ years of technical implementation experience

What would be great to have:

• Experience in the Financial Services Industry and an understanding of relevant

• compliance standards and regulations.

• Certification in AI/ML or relevant technologies.

• Experience with reporting tools like Splunk, SSRS, Cognos, and Power BI