LocationThis 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.
The base compensation range for this role in the posted location is: $82,082 - $193,440.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
