# AI Analyst, Sr – AI Forward Deployed Engineer at Pathward

> Remote · United States · Senior · Software engineering · open. Source: https://alderhq.app/jobs/greenhouse%3Apathward%3A6239487004 (read 2026-11-03).

## Facts (observed)

- Company: [Pathward](https://alderhq.app/companies/pathward)
- Location text: Remote; Remote; USA
- Where it can be done from (inferred): Remote · United States (evidence: "Remote role open worldwide")
- Posted: 2026-11-03 (0 days ago)
- First seen by alder: 2026-11-03 · last verified: 2026-11-03
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/pathward/jobs/6239487004
- Skills listed (inferred): AWS, GCP, Azure, LLMs

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

We are a hybrid, remote-office company dedicated to growing our talent anywhere!

We have onsite locations in: Sioux Falls, SD, Phoenix, AZ, Louisville, KY, Troy, MI, Franklin, TN, Easton, PA.

At Pathward, we take tremendous pride in our purpose to create financial inclusion for all™. We are a financial empowerment company that works with innovators to increase financial availability, choice, and opportunity for all. We strive to remove barriers that traditional institutions put in the way of financial access, and promote economic mobility by providing responsible, secure, high quality financial products.

We are a team of problem solvers and innovators who celebrate our differences and know that our unique perspectives make us stronger and well-positioned for success. We celebrate, and embrace, our team members through our \*HUMBLE\*HUNGRY\*SMART approach, and we believe that we are strongest when we embrace the voices of our employees, customers, partners, and the communities we serve.

### About the Role

The AI Forward Deployed Engineer ensures Pathward’s AI investments deliver real, operational impact. This forward‑deployed, customer‑embedded role owns deployment readiness, data integrity, and solution delivery, working closely with AI Engineers, Data Scientists, and Architecture and Platform Engineering teams to deploy, adopt, and scale AI solutions responsibly across the enterprise. This role is deployment centric - owning the technical and operational success of AI solutions in real business environments.

Success in this role is defined by delivering deployment‑ready AI solutions that are adopted by stakeholders, enabling business‑defined outcomes, and scaling predictably across the enterprise.

### What You Will Do

- Serve as the technical bridge between stakeholders and AI/engineering teams, translating business needs into clear 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 other dependencies to ensure environments are ready for production AI deployments.
- Identify and mitigate technical, operational, scalability, reliability, regulatory, and compliance risks throughout the deployment lifecycle.
- Evaluate data availability, quality, lineage, and governance, partnering with data and business teams to address gaps that could impact AI implementation.
- Assess business processes for readiness, ensuring they are sufficiently defined, stable, and measurable to support 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 and troubleshoot issues in pre-production and live environments.
- Enable successful business adoption through documentation, demonstrations, walkthroughs, knowledge transfer, and ongoing stakeholder feedback.
- Capture learnings and establish repeatable patterns, practices, and playbooks that improve the scalability and reusability of AI implementations across the enterprise.
### What You Will 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 (e.g., solution engineering, implementation, 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 (e.g., MLOps, model lifecycle, LLM‑based solutions).
- Strong communication skills across technical and non‑technical stakeholders.
### Preferred Qualifications

- Experience deploying AI or advanced analytics solutions in regulated environments (financial services, fintech, healthcare, etc.).
- Familiarity with cloud platforms (Azure, AWS, or GCP) and enterprise data ecosystems.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Apathward%3A6239487004 and the date you read it. Observed facts come from the employer's public job board; location reach, level, family and skills are inferences.