AI Solution Engineer

Job Description : AI Solution Engineer

Location : INDIA

Full Time

Job Posting Title : AI Solution Engineer

What does a AI Solution Engineer do ?

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.