AI Engineer - job 1 of 6

As an AI Engineer at Capco, you'll manage the deployment of our GenAI chat platform, develop roadmaps for future implementations, and work with diverse technical and business teams to create innovative GenAI solutions across various business units.

Candidates should have at least 4 years of AI engineering experience, strong project management skills, proficiency in programming languages like Python and NodeJS, and a background in cloud technologies. A bachelor's degree in computer science, engineering, or a related field is also required.

Capco offers a culture focused on innovation, rapid learning, and minimal bureaucracy, ensuring that AI Engineers can take on challenges and advance their careers quickly. Our diverse workplace fosters creativity and collaboration among team members.

AI Engineers at Capco work with GenAI frameworks, REST APIs, and various cloud environments such as AWS or Azure. They also focus on coding in languages like Python and NodeJS, participating in prototype development, and evaluating emerging technologies.

Capco provides competitive benefits, including medical, dental, and vision insurance, a 401(k) plan, tuition reimbursement, and a work culture that emphasizes innovation and collaboration, so you can contribute effectively while enjoying your work.

Certainly! In my previous roles, I have been involved in deploying GenAI solutions, focusing on knowledge management and personalized content retrieval, which helped improve user engagement and efficiency.

I place a high value on communication and transparency. By fostering an open dialogue with both technical teams and business units, I ensure that everyone is aligned with project goals and can contribute their insights effectively.

I perform thorough market research, assess the potential benefits and risks, and create proof of concepts to evaluate how new technologies could improve our existing systems or solutions.

I approach code reviews as a collaborative learning experience. I provide constructive feedback while also encouraging my team to share their insights, which helps improve the overall quality of our codebase.

I've managed several projects focused on deploying AI solutions, including a chat platform aimed at enhancing customer service through AI-driven interactions, which resulted in improved response times.

Prompt engineering is about crafting inputs that effectively guide AI models towards generating desired outputs. By refining prompts, we can enhance the quality of responses from models and significantly improve functionality.

I have designed and implemented REST APIs for several applications, allowing seamless integration between AI solutions and existing systems while ensuring data security and efficiency in communication.

I encourage an iterative learning process by involving junior engineers in discussions where they can ask questions and express their ideas, providing them with guidance to make informed design choices.

In my experience, analyzing the cost-benefit trade-offs involves evaluating the implementation costs of GenAI solutions against the potential productivity gains and savings they can provide in the long term.

One significant challenge was integrating a new AI system with legacy software. I worked closely with stakeholders to devise a hybrid approach that maintained functionality while gradually transitioning to the new solution.