Senior AI Analyst – AI Forward Deployed Engineer

Pathward

. Serve as the technical bridge between stakeholders and AI/engineering teams, translating business needs into technical, data, and solution requirements .

Posted 11/3/2026full-timeRemote • United StatesSenior💰 $86,000 - $145,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in translating business needs into technical requirements for AI solutions, with a strong focus on data quality, governance, and deployment readiness. Proficient in collaborating with cross-functional teams to ensure successful AI implementation and adoption.

Highest-signal resume keywords

AI/ML PlatformsData GovernanceCloud Platforms (Azure, AWS, GCP)Solution EngineeringRegulatory Compliance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data-Driven SystemsMLOpsModel LifecycleAI Solution DeploymentData Pipeline Integration

Soft Skills

Strong Communication SkillsStakeholder Engagement

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceBachelor’s Degree in EngineeringBachelor’s Degree in Information Systems

Industry Keywords

AI OpportunitiesProduction DeploymentOperational RisksImplementation GapsBusiness Process Readiness

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Serve as the technical bridge between stakeholders and AI/engineering teams, translating business needs into technical, data, and solution requirements
Partner with business, product, and technology teams to understand workflows, identify high-value AI opportunities, and align solutions with business outcomes
Assess infrastructure, security, access controls, integrations, and dependencies for production AI deployment readiness
Identify and mitigate technical, operational, scalability, reliability, regulatory, and compliance risks throughout the deployment lifecycle
Evaluate data availability, quality, lineage, and governance, and address implementation gaps
Assess business-process readiness for AI-enabled automation and decision-making
Configure, integrate, and deploy AI solutions, including models, workflows, data pipelines, integrations, and supporting services
Translate AI prototypes and proofs of concept into scalable, production-grade solutions
Troubleshoot issues in pre-production and live environments
Enable business adoption through documentation, demonstrations, walkthroughs, knowledge transfer, and stakeholder feedback
Establish repeatable patterns, practices, and playbooks to improve AI implementation scalability and reusability

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent relevant experience
Typically, 5+ years of experience in customer-facing or deployment-oriented technical roles, such as solution engineering, implementation, or forward-deployed roles
Strong understanding of data-driven systems and AI/ML platforms
Ability to translate ambiguous business needs into clear technical and data requirements
Familiarity with AI/ML concepts, including MLOps, model lifecycle, and LLM-based solutions
Strong communication skills across technical and non-technical stakeholders
Preferred: Experience deploying AI or advanced analytics solutions in regulated environments
Preferred: Familiarity with cloud platforms such as Azure, AWS, or GCP and enterprise data ecosystems
Preferred: Experience supporting solutions from pilot through production rollout

Benefits

Comp & perks

Annual performance-based incentive opportunity
Health insurance
401(k) retirement benefits
Life insurance
Disability benefits
Paid time off
Comprehensive benefits package for eligible employees