Senior AI Solution Architect

Groundswell is a premier technology integrator resolutely committed to solving the most complex challenges facing federal agencies today. Our name, Groundswell, represents our commitment to be an unstoppable, seismic change in government. Ours is a small company culture with big company reach and results.

Are you ready to be audacious, be bold and drive change at a rapid paceJoin us, where we’ll make a greater impact together.

• What You'll do :
• Skills :
• Certification :
• Why You’ll Never Want to Leave :
• Comprehensive medical, dental, and vision plans
• Flexible Spending Account
• 4% 401K Match (immediate vesting)
• Paid Time Off
• Tuition reimbursement, certification programs, and professional development
• Flexible work schedule
• On-site gym and childcare optionThe salary range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for any applicable geographic differential associated with the location at which the position may be filled. At Groundswell, it is not typical for an individual to be hired at or near the top of the range for their role, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is : $82,252.00 - $157,886.00
• NOTE
• Groundswell does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Groundswell, and Groundswell will not be obligated to pay a placement fee.Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.Read a copy of the .
• Additional Resources
• : Disability Accessibility Accommodation : If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact us at hr@gswell.com or 703-639-1777.
• What You'll Do :
• In a customer-facing role, the Senior AI Solution Architect focuses on designing, developing, and deploying custom and pre-built Enterprise AI applications. This role requires both big-picture solution design and hands-on implementation expertise.
• Responsibilities :
• Engage directly with customers post-sales to configure and implement full-stack AI solutions.
• Drive discussions on architecture and engineering, explaining platform capabilities and interoperability.
• Design and implement reference architectures for scalable and reusable solutions.
• Develop technical specifications, documentation, and user support guides.
• Assess technical risks and develop mitigation strategies.
• Collaborate with engineering and product teams to incorporate customer feedback.
• Travel to customer sites (up to 30%).
• Required Qualifications :
• Bachelor’s degree in engineering, computer science, or related field.
• 8+ years of system / data integration, development, or enterprise / cloud software implementation.
• Deep understanding of enterprise architecture and application integration (APIs, Queues, Streams).
• Hands-on expertise in Big Data, Distributed Systems, and Cloud Architectures (AWS, Azure, GCP).
• Proficiency in Python, JavaScript, and / or Java.
• Experience with relational and NoSQL databases.
• Strong organizational, troubleshooting, and problem-solving skills.
• Excellent communication and presentation skills
• Must be a U.S. Citizen per contract requirements
• Must be local to the DC Metro area and able to be onsite in McLean, VA 5 days a week
• Preferred Qualifications :
• Experience with C3 AI platform preferred.
• Expertise in Postgres, Cassandra.
• Experience with Kafka, Kinesis.
• Experience with Kubernetes or OpenShift deployments.
• Knowledge of DataOps and MLOps in production environments.
• Understanding of ML algorithms and vector databases.
• Familiarity with MLFlow, KubeFlow, SageMaker, or Azure MLStudio.
• Knowledge of information and infrastructure security concepts.

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