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.

This is a hybrid role located at Long Beach, CA.

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.

• 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.

• 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, Tensor Flow, Lang Chain, Llama Index).
• 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/No
  
  SQL databases.