Sr. Forward Deployed Engineer at Alkami Technology
- Company: Alkami Technology
- Location: US Remote
- Salary: $128K – $160K
- Job type: full time
- Workplace: remote
- Posted: 2026-10-26
All open roles at Alkami Technology
Job description
Alkami is the digital sales and service platform provider for U.S. banks and credit unions. Our unified Platform integrates onboarding, digital banking, and data and marketing—each solution can stand alone, but together they deliver more—to help institutions onboard, engage, and grow relationships. As the future shifts toward Anticipatory Banking, we help data-informed bankers meet the moment with technology that drives action. Founded in 2009, we continue to be recognized for our intentional culture and tremendous growth (Best Place to Work in Fintech; Best & Brightest to Work For Nationally; and Comparably’s Best Company Culture, Best Career Growth, Best Engineering Team, and Best Places to Work in Dallas, among others). We’re building a culture where each Alkamist can perform to their highest potential, and we’re always on the lookout for the best and brightest minds. If you’re ready to experience the power of alchemy - transforming the ordinary into the extraordinary - come join one of the fastest growing SaaS companies in the U.S. As a remote-first company, most of our positions can be remote in the US, except for key roles, which will be indicated in the Job Title. Follow us on Glassdoor and LinkedIn ! The Sr. Forward Deployed Engineer independently drives the delivery of internal AI, automation, data, and workflow solutions for Alkami's business and functional teams. This hands-on individual contributor translates complex business needs into technical designs, production software, AI-enabled workflows, integrations, dashboards, and reusable capabilities. The role participates in the design process from beginning to end, demonstrates deep technical and business domain knowledge, and serves as a key partner to Revenue, Marketing, Product, Engineering, AI and Data, and other stakeholders. The role owns moderately complex initiatives through discovery, design, build, testing, deployment, adoption, and continuous improvement; contributes to the roadmap and technical standards; supports production systems; and helps other team members build their capabilities.

 Essential Duties & Responsibilities Lead discovery with business and functional stakeholders to understand workflows, goals, constraints, and pain points; translate findings into requirements, technical designs, implementation plans, acceptance criteria, and measurable outcomes. Independently design, build, test, and deploy moderately complex AI agents, skills, dashboards, automations, data pipelines, and integrations that improve team productivity and business outcomes. Participate in the entire solution lifecycle, from prototyping and feasibility testing through production implementation, adoption, support, and continuous improvement. Write, review, and maintain clean production code with automated tests, useful documentation, clear ownership, and alignment to team development standards. Apply API-first and integration-focused approaches to connect business applications, systems of record, relational databases, and internal AI capabilities using secure and maintainable designs. Map data flows and implement authentication, authorization, validation, logging, error handling, monitoring, and data provenance for integrations and AI-enabled workflows. Build and maintain reusable code, libraries, workflow components, integration patterns, evaluation approaches, and implementation guides that can be adopted by other teams. Build solutions that operate reliably in production and, when appropriate, read from and write to systems of record. Own testing, evaluations, security, data validation, observability, error handling, human-in-the-loop controls, and production support. Use AI tools, coding agents, agent builders, and workflow automation as a default part of building, testing, documenting, analyzing, and operating software. Partner with Product, Engineering, AI and Data, and functional teams to distinguish configuration needs from product or platform gaps and reco
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