AI Architect

Job Title: AI Architect

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Location

This is a hybrid role located at Seattle, WA.

About the job you're considering

We are seeking a highly skilled AI Architect/Developer hybrid to bridge the gap between AI strategy and production-grade implementation. This individual will be responsible for designing scalable AI ecosystems, selecting appropriate model architectures, and directly contributing to the development of custom AI solutions, pipelines, and integrations.

Your role

• Translate business requirements into robust, high-performance AI architectural blueprints.
• Write clean, modular, and maintainable production code.
• Conduct model tuning, quantization, and pruning to ensure models meet performance thresholds.
• Act as a lead developer to mentor junior staff and ensure best practices in code quality and model security.
• Comfortable working within an Agile/Scrum framework with frequent delivery milestones.
• Commitment to maintaining comprehensive architectural documentation, including data flow diagrams and API specifications.
• Strict adherence to data privacy standards and secure AI development practices.
• Proven delivery of ninja with robust portfolio of quantifiable success stories.

Your skills and experience

• Experience designing scalable machine learning infrastructure (on-prem, cloud-hybrid, or multi-cloud environments).
• Minimum of 10 years of experience designing, developing, and delivering enterprise-scale technology solutions, including AI/ML architectures, with a proven ability to translate business requirements into secure, scalable, and high-performance AI platforms.
• Ability to evaluate and select the right LLMs, SLMs, or traditional ML models based on latency, cost, and accuracy requirements.
• Expertise in integrating AI services with existing enterprise software ecosystems, including security, compliance, and data governance frameworks.
• Proficiency in Python-based frameworks (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex).
• Hands-on experience with CI/CD for AI, model versioning, and monitoring tools (e.g., MLflow, Kubeflow, Weights & Biases).
• Strong background in RESTful API development (FastAPI, Flask) and data pipeline architecture (Apache Airflow, Kafka, Spark).
• Deep understanding of the underlying principles of neural networks and transformer architecture.
• Ability to interpret and optimize model performance using formulas related to loss functions and optimization.
• Strong proficiency in Python, SQL, and familiarity with C or Go for high-performance components.
• Expertise in containerization and orchestration using Docker and Kubernetes.
• Experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and traditional RDBMS/NoSQL databases.