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This Subcontract opportunity from California was posted on July 30, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Financial & Rate Structure Modeling Software Support

Closed
State & Local

Contract Overview

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

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NAICS: 541512
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FY27_EOPSS_ITS87_Artificial Intelligence Engineer
Solicitation # BD-27-1044-EPS17-OTIS-135351
The Executive Office of Public Safety and Security (EOPSS) is seeking a Cloud AI Engineer to support the enhancement and management of a system-wide criminal justice data platform. This role is focused on accelerating AI adoption and implementing enterprise-scale solutions to integrate data from courts, police departments, and custodial institutions. The engineer will be responsible for architecting retrieval-augmented generation (RAG) solutions using vector databases and embedding models, integrating Model Context Protocol (MCP) servers, and managing AWS infrastructure using Terraform and CloudFormation. Key security requirements include implementing AWS IAM and Snowflake Role-Based Access Control (RBAC). The engagement is a full-time position of 37.5 hours per week, running through June 30, 2027, with a maximum all-inclusive hourly vendor bill rate of $125. Candidates must possess at least 10 years of experience in AWS cloud and data solutions. While the primary location is Milford, Massachusetts, there is a preference for candidates residing in Massachusetts or those able to travel to Milford, Boston, or Middleborough. Selected candidates must complete CORI and DCJIS fingerprinting requirements in Chelsea, Massachusetts. This procurement is eligible for the Small Business Purchasing Program, and vendors may submit a maximum of eight resumes via the COMMBUYS portal.
Executive Office of Public Safety & Security

POSTED

about 18 hours ago

DEADLINE

in 13 days

AI Contract Overview

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The contract seeks specialized software tools or technical support to model complex fee structures including tiered, flat, and percentage-based systems, with a focus on accurately forecasting the financial impact of these structures on revenue. The work requires advanced analytical capabilities to simulate how changes in fee configurations affect overall income streams, ensuring the Finance Department of the City of Newport Beach can make informed decisions regarding rate design and fiscal planning. The recipient must deliver solutions that are precise, scalable, and capable of handling dynamic financial variables under real-world constraints. This is a subcontract opportunity under NAICS code 541512, with a response deadline of August 31, 2026, and a posting date of July 30, 2026. While no specific set-aside type or organizational requirements are indicated, the performance location and solicitation details are linked to the City of Newport Beach's Finance Department, indicating the end-use of the deliverables will be within municipal financial operations. Bidders must be prepared to provide not only technical software capabilities but also expert support in interpreting modeling outputs and aligning them with local revenue management objectives.

General Info

Develop specialized software to model tiered, flat, and percentage fee structures for Newport Beach Finance Department revenue forecasting.

Documents

This scope was carved out of 27-01.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Solid Waste Franchise Service Fee & Rate Structure Assessment

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyCalifornia → Finance Department of City of Newport Beach
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Provide specialized software tools or technical support for modeling tiered, flat, and percentage-based fee structures and forecasting revenue impacts.

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