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AI/ML Infrastructure Development

Active
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The contract focuses on the development and maintenance of secure AI and machine learning infrastructure within the AWS GovCloud environment. This includes building software factories, establishing model deployment pipelines, and ensuring integration with ESMC data systems to support advanced operational capabilities. The work is designated as a subcontract under NAICS code 541512, which pertains to computer systems design services. Awarded by the Department of Defense through its DCSO Philadelphia office, the contract requires execution at the Fort Belvoir location, supporting critical defense operations. The scope emphasizes security, scalability, and seamless data system integration to enhance AI/ML operational readiness in a government cloud setting. This effort is essential to advancing secure AI deployments aligned with defense mission needs.

General Info

Develop and maintain secure AI/ML infrastructure in AWS GovCloud for Defense at Fort Belvoir.

Agency

Department Of Defense → Dcso PhiladelphiaView Agency

NAICS

541512 - Computer Systems Design ServicesView NAICS

Place of Performance

Fort Belvoir, VA, 22060, USA

Set-Aside

NONE

Documents

This scope was carved out of SP4709-25-F-0067P00003.

The full solicitation package (1 document), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Enterprise Hosting Support Services

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Timeline

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Organization & Contact Information

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AgencyDepartment Of Defense → Dcso Philadelphia
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Defense → Dcso Philadelphia
View Agency Profile
Office AddressN/A
ContactsNo contact information available

Full Description

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Develop and maintain secure AI/ML infrastructure in AWS GovCloud, including software factories, model deployment pipelines, and integration with ESMC data systems.

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