AI Technical Architect

Capco • Charlotte, NC

34d • Hybrid

About The Position

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 Architect, 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 visionary and highly skilled Generative AI Architect to lead the design and implementation of our next-generation AI systems, with a strong focus on foundation models and agentic AI. This role is pivotal in defining the architectural blueprint for enterprise-scale generative AI solutions, ensuring they are robust, scalable, secure, and aligned with our strategic business objectives. The ideal candidate will be a thought leader, capable of translating complex business challenges into innovative AI architectures and guiding cross-functional teams from conceptualization to production deployment.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 10+ years of progressive experience in software architecture, with at least 2-3 years specifically focused on Generative AI and Machine Learning.
• Demonstrated expertise in designing and implementing AI architectures with a strong focus on Generative AI and Agentic AI technologies.
• Profound understanding of various foundation models (LLMs, vision models, multimodal models) and their underlying architectures (e.g., Transformers).
• Hands-on experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
• Strong programming skills in Python is essential, with experience in relevant AI/ML frameworks (e.g., TensorFlow, PyTorch).
• Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services (e.g., Amazon SageMaker, Azure Machine Learning, Google Cloud AI Platform, Vertex AI).
• Familiarity with MLOps principles and tools for deploying, monitoring, and managing AI models and agentic systems in production (e.g., MLflow, Kubeflow).
• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Azure AI Search) and techniques for processing and ingesting unstructured data.
• Excellent communication, interpersonal, and leadership skills, with the ability to influence and drive technical decisions.
• Strong analytical and problem-solving abilities.
• Willingness to work in the Charlotte office 3 days per week.

Responsibilities

• Define and evolve the enterprise-wide architectural vision and strategy for Generative AI and agentic systems, aligning with overall business goals and technology roadmaps.
• Lead the design of modular, reusable, and scalable architectural patterns for GenAI and agentic applications across various domains.
• Design and implement robust, secure solution patterns that can be operationalized across enterprise environments.
• Deep expertise in various foundation models (e.g., LLMs, vision models, multimodal models) including their architectures, strengths, limitations, and fine-tuning techniques.
• Evaluate, select, and integrate appropriate foundation models for specific use cases, considering factors like performance, cost, and ethical implications.
• Develop strategies for model pre-training, fine-tuning, and continuous improvement.
• Architect and implement intelligent agentic AI systems using frameworks like LangChain, LangGraph, CrewAI, AutoGen, or similar.
• Design complex agentic workflows, including planning, reasoning, tool integration, memory management, and human-in-the-loop interactions.
• Lead the integration of agentic AI solutions with existing enterprise systems and define integration standards (e.g., RESTful APIs, microservices).
• Apply advanced prompt engineering techniques to optimize AI model performance and steer outputs towards desired outcomes, minimizing bias and hallucinations.
• Oversee orchestration of AI components and services, including LLM APIs, vector databases, and external tools.
• Develop and implement Retrieval Augmented Generation (RAG) based solutions for enhanced contextual understanding and factual accuracy.
• Design and build cloud-native, containerized infrastructure (e.g., Kubernetes, ECS, EKS on AWS, Azure, GCP) for deploying GenAI models and agentic systems at scale.
• Implement robust MLOps pipelines for the continuous integration, delivery, deployment, monitoring, and management of AI models in production.
• Ensure AI solutions comply with regulatory requirements, data privacy, and ethical AI standards.
• Stay abreast of the latest advancements in AI, machine learning, deep learning, and agentic systems, and apply this knowledge to drive innovation.
• Rapidly develop Proofs of Concept (PoCs) and iterate solutions using an agile, experimental approach without compromising architectural integrity or long-term scalability.
• Serve as a technical expert and mentor to junior AI engineers and architects, fostering a culture of continuous learning and improvement.
• Contribute to internal workshops, knowledge sharing, and external forums as a thought leader.
• Collaborate effectively with cross-functional teams including product managers, data scientists, software engineers, security, and business stakeholders.
• Articulate complex technical concepts to diverse audiences, both technical and non-technical.
• Maintain detailed architectural documentation and operational playbooks.

Benefits

• We offer highly competitive benefits, including medical, dental, and vision insurance, a 401(k) plan, tuition reimbursement, and a work culture focused on innovation and creation of lasting value for our clients and employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Professional, Scientific, and Technical Services
• Number of Employees: 1,001-5,000 employees