AI/ML Integration Specialist - AFTAS Pro

Socket.dev; Washington (District of Columbia); On-site; USD 120,000 - 180,000; Full time

Job summary

Socket.dev in Washington, DC is hiring an AI/ML Integration Specialist to provide technical direction for bringing approved AI capabilities into an existing federal acquisition enterprise, its toolset, data, and accredited infrastructure.

This role focuses on integration over model development, addressing schema alignment, API and connector configuration, data readiness, and building verification and monitoring frameworks to earn government trust in AI-driven outputs.

Qualifications

• 5+ years integrating AI/ML into enterprise environments, including DoD/federal contexts.
• Master's degree in CS or data science, or bachelor’s with equivalent experience.
• Active Secret clearance (interim Secret with approval).

Responsibilities

• Evaluate AI tools for integration suitability against mission requirements.
• Analyze architectures to determine value and risk of AI integration.
• Draft technical roadmaps for phased AI adoption.
• Identify and document integration risks, interoperability challenges, and resource needs.
• Define data mapping strategies between source systems and AI tools.
• Provide design support for modifying data pipelines to meet AI requirements.
• Draft data quality, security and compliance procedures for AI consumption.
• Configure APIs and data connectors for AI services with security teams.
• Document technical requirements for interfacing with AI models.
• Validate that integrated AI solutions match user workflows and not just diagrams.
• Design continuous verification frameworks for security and performance.
• Develop test and evaluation criteria for mission objectives.
• Conduct ongoing monitoring and vulnerability assessments of AI outputs.

Skills

AI/ML integration

API integration

Data pipeline engineering

Data mapping

Security/compliance

DoD/federal frameworks

Stakeholder communication

Continuous verification

Vulnerability assessment

Technical documentation

Education

Master's degree in computer science or data science

Bachelor's degree with equivalent experience

Tools

APIs

Data connectors

Data mapping tools

Job description

Description

We are hiring an AI/ML Integration Specialist to provide technical direction for bringing approved AI capabilities into an existing federal acquisition enterprise — its toolset, its data, and its accredited infrastructure. Worth being direct about scope: this is an integration role, not a model development role. The hard problems here are schema alignment, API and connector configuration, data readiness, and building the verification and monitoring frameworks that let a security-conscious customer trust an AI-driven output. If you want to train foundation models, this is not that job. If you want to make AI actually work inside a large regulated enterprise, it is.

What You'll Get to Do as a AI/ML Integration Specialist:

• Evaluate existing and emerging AI tools for integration suitability against real mission requirements.
• Analyze current system architectures to determine where AI integration produces value and where it introduces unacceptable risk.
• Draft technical roadmaps supporting phased AI adoption, sequenced by dependency and risk rather than by novelty.
• Identify and document integration risks, interoperability challenges, and resource requirements.
• Define data mapping and schema alignment strategies between source systems and AI tools.
• Provide design support for modifying data pipelines to meet AI requirements.
• Draft data quality, security, and compliance procedures that make enterprise data fit for AI consumption.
• Configure APIs and data connectors for AI services, working alongside platform and security teams.
• Document and define technical requirements for interfacing with AI models.
• Validate that integrated AI solutions actually match how users work, not just how the architecture diagram says they should.
• Design and document continuous verification frameworks that keep AI components secure, usable, and performing within established parameters.
• Develop test and evaluation criteria the government can use to validate that integrated AI systems meet mission objectives.
• Conduct ongoing technical monitoring and vulnerability assessment, verifying the accuracy, safety, and reliability of AI-driven outputs.

Requirements

• 5+ years integrating AI and machine learning capabilities into enterprise environments, with at least some of that work inside DoD or federal frameworks.
• Master's degree in computer science or data science, or a bachelor's degree with equivalent additional experience.
• Active Secret clearance (interim Secret considered with approval).
• Hands-on API and data connector configuration, schema mapping, and data pipeline engineering.
• Ability to explain AI capability, limitation, and risk to non-technical senior stakeholders without overselling either.

Preferred Qualifications:

• WS Certified Machine Learning Engineer – Associate, or AWS Certified AI Practitioner. Holders of the retired AWS Certified Machine Learning – Specialty are equally welcome — that credential remains active for three years from the date earned.
• Google Cloud Professional Machine Learning Engineer, or comparable current cloud ML credential.
• Experience with AI test and evaluation, continuous verification, or security monitoring in an accredited government environment.
• Prompt engineering and AI-enabled workflow design experience.
• Familiarity with federal AI governance and compliance expectations.