ABOUT THE TEAM:

At the Capco Technology Delivery Center, we are dedicated to the financial services industries. Our professionals combine innovative thinking with unrivalled industry and domain expertise to offer our clients consulting expertise, complex technology and package integration, transformation delivery, and managed services, to move their organizations forward. Through our collaborative and efficient approach, we help our clients successfully innovate, increase revenue, manage risk and regulatory change, reduce costs, and enhance controls. Our teams stay at the forefront of industry trends and technologies that are driving innovation. From strategy to launch, we are adept at delivering across the full product lifecycle.

ABOUT THE JOB:

As a member of the Capco Technology Delivery Team, you’ll bring practical knowledge of agile development methodologies and engineering best practices. As an AI Engineer, you’ll play an integral role using your experience and skills to contribute to the quality and implementation of our projects.
We are seeking a highly skilled and experienced Senior GenAI Engineer who will be instrumental in designing, developing, and deploying modern generative AI solutions, leveraging expertise in foundation models, agentic AI systems, and full-stack application development. You will work across the entire AI lifecycle, from research and prototyping to production deployment and monitoring, contributing to high-impact transformative projects.

What You’ll Get to Do:

• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Mentor junior engineers, share knowledge, and foster a culture of technical excellence

What You’ll Bring with You:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field
• 5+ years of experience in software development with a strong focus on AI/ML
• Proven experience in building and deploying Generative AI models (e.g., LLMs, diffusion models) in production environments
• Demonstrated expertise in designing and implementing agentic AI systems and multi-agent architectures
• Strong understanding and practical experience with the Model Context Protocol (MCP) for AI system integration
• Solid experience with full-stack application development
• Extensive experience with cloud platforms (AWS, Azure, or GCP) for AI/ML deployments and general application hosting
• Experience with LLMOps tools and practices (e.g., Langfuse, Langsmith, etc)
• Excellent problem-solving, analytical, and communication skills
• Ability to work independently and collaboratively in a fast-paced, agile environment
• Willingness to work in the New York office 3 days/week.

• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Mentor junior engineers, share knowledge, and foster a culture of technical excellenc