Alkami Technology
Alkami Technology

Senior Forward Deployed Engineer

$128–160kRemote, USRemoteSeniorFull-time

Posted 5 days ago

The role in short

Builds and deploys internal AI agents, automations, and integrations for Alkami's own business and functional teams to improve productivity.

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 recommend practical, scalable solutions.
  • Design and execute evaluations, human-in-the-loop controls, and responsible AI safeguards; validate AI-assisted work before it is used in business processes.
  • Set up and maintain environment configurations, monitor system health, investigate production issues, and implement proactive measures to improve reliability and performance.
  • Track adoption, usage, hours saved, quality, and other agreed outcomes; use stakeholder feedback and operational data to prioritize improvements.
  • Contribute to the canonical set of approved skills, agents, dashboards, templates, and documentation for the supported function; retire or consolidate duplicative solutions when appropriate.
  • Actively participate in the weekly FDE forum by sharing demos, lessons learned, reusable patterns, technical challenges, and business outcomes; contribute to shared standards for architecture, security, evaluations, and responsible AI.
  • Provide training, technical support, and mentoring to junior engineers, business builders, and functional partners; share lessons learned with the FDE and broader engineering community.
  • Communicate technical options, tradeoffs, risks, dependencies, progress, and decisions clearly to technical, nontechnical, and executive stakeholders.
  • Dedicate approximately 20% of time to improving Alkami’s shared AI platform by contributing reusable connectors, components, skills, evaluations, guardrails, documentation, and patterns that enable other teams to build more effectively.
  • Respond promptly to production incidents or on-call issues, including troubleshooting and resolving critical disruptions to minimize downtime and business impact.
  • Apply security, privacy, accessibility, change-management, and responsible AI standards; protect company, customer, and financial data
  • Adhere to and uphold Alkami's Values.

Recommended Experience & Education

Minimum Years of Experience

Typically requires a minimum of 5 years of related experience; or 3 years and an advanced degree.

Education Level

Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.

Knowledge, Skills, & Qualifications

Required

  • Requires a minimum of 5 years of related experience in software development, technical implementation, data systems, automation, or a related field; or 3 years and an advanced degree.
  • Strong programming skills in Python, TypeScript, JavaScript, Java, C#, or a comparable language, with proven experience shipping and supporting production software, data systems, or workflow automation.
  • Experience working directly with business, functional, customer, or partner stakeholders to translate ambiguous needs into technical approaches and measurable outcomes.
  • Experience building or integrating AI-enabled workflows, agents, or automations using coding assistants, agent or workflow builders, prompt and tool design, evaluations, human review, and safeguards for sensitive data; applies AI-assisted workflows to enhance productivity in code generation, testing, documentation, and refactoring while validating outputs.
  • Demonstrated daily use and a portfolio of agents or automations are expected; general familiarity with AI tools is not sufficient.
  • Have shipped at least one production AI or agent-based system that was adopted by another team and continues to be actively used, with measurable value, clear ownership, and ongoing support.
  • In-depth understanding of the software development lifecycle, including design, development, testing, cloud-native deployment, monitoring, and production support; working knowledge of version control, code review, automated testing, and CI/CD practices.
  • Experience with SQL and NoSQL databases, data structures, caching mechanisms, data quality, and troubleshooting or optimizing data access and application performance.
  • Understanding and practical application of REST API best practices and experience integrating APIs, webhooks, authentication and authorization protocols, business applications, and systems of record.
  • Experience developing unit tests, UI automation tests, integration tests, or evaluations for AI-enabled workflows; familiarity with monitoring and supporting production systems, identifying and resolving issues, and tracking performance or adoption measurements.
  • Collaborates effectively within an agile or iterative framework with a problem-solving attitude and willingness to take a variety of approaches.
  • Excellent analytical and time-management skills, with a proven ability to deliver value independently, manage dependencies, and adapt to changing priorities.
  • Strong written and verbal communication skills, with demonstrated experience providing technical input, explaining complex concepts to technical and nontechnical audiences, and working cross-functionally with engineering, product, AI and Data, and wider organizational initiatives.
  • Ability to participate in production support or an on-call rotation when required by the supported solution.
  • Understanding of secure development, access controls, data privacy, operational reliability, and responsible AI practices when working with company, customer, and financial data.

Preferred

  • Experience working with SaaS offerings in the technology and financial industries, including banking, credit unions, fintech, or another regulated environment.
  • Experience in a forward-deployed, consulting, implementation, customer engineering, business systems, revenue operations, marketing operations, or other stakeholder-facing technical role.
  • Experience building and deploying applications or integrations on Amazon Web Services using Kubernetes, event-driven services, infrastructure as code, or comparable cloud technologies.
  • Experience with modern data warehouses, CRM, customer success, marketing, sales, or conversation-intelligence data and workflows.
  • Experience in observability, OpenTelemetry, performance optimization, or operational reliability practices.
  • Working knowledge of MCP or comparable tools for connecting AI systems to business applications, or experience contributing to an internal AI platform, shared engineering foundation, or community of practice.

The salary range for this position is: $128,000 - $160,000

Cool Things to Know

Not Just Any Company: Alkami has an awesome diverse and inclusive environment. We have a FUN culture and offer great benefits, including remote-first environment, unlimited paid time off, 401(k) with employer match, and more.

Work Authorization: We cannot offer employment sponsorship at this time. Candidates must be eligible to work in the US for full-time employment.

Recruiters: We are not looking for outside recruiting firms to help us in this search. Thank you for understanding.

Pay Transparency: As of January 1, 2023, new states and locales have enacted pay equity laws that require more pay transparency by employers in the following states: California, Colorado (effective January 1, 2021), Connecticut, Maryland, Nevada, New Jersey, New York, Ohio, Rhode Island and Washington.

The Important Stuff

Alkami Technology is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: Alkami is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at Alkami are based on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. Alkami will not tolerate discrimination or harassment based on any of these characteristics. Alkami encourages applicants of all ages.

Prep for this interview

5 questions likely to come up at Alkami Technology, each matched to a line in this posting.

  1. 1Coding
    They wrote: “Strong programming skills in Python, TypeScript, JavaScript, Java, C#, or a comparable language, with proven experience shipping and supporting production software, data systems, or workflow automation.”

    Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.

    How to answer

    Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.

    1. Read with a proper CSV parser; check the header first
    2. Validate each row and collect errors, not crash on the first one
    3. Send in batches with retries and a clear report at the end
    4. Write one or two quick tests for the parsing

    Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.

  2. 2Integrations and APIs
    They wrote: “Understanding and practical application of REST API best practices and experience integrating APIs, webhooks, authentication and authorization protocols, business applications, and systems of record.”

    Walk me through connecting our product to a customer's internal system that has no documentation.

    How to answer

    Why they ask: This happens weekly in the job. They want a calm, step-by-step method.

    1. Find who owns the system and get read access to a test environment
    2. Watch real traffic or logs to learn the data shapes
    3. Build a thin adapter with logging around every call
    4. Agree on how failures get reported, and who fixes what

    Tip: Talk about finding the owner of the system first. The code is the easy part.

  3. 3Discovery and scoping
    They wrote: “Track adoption, usage, hours saved, quality, and other agreed outcomes; use stakeholder feedback and operational data to prioritize improvements.”

    How do you decide what to build first when a customer wants ten things?

    How to answer

    Why they ask: FDEs have limited weeks per customer. This tests judgment about value, effort and risk.

    1. Score each request by business value and by effort, with the customer in the room
    2. Pick one item that proves value fast and unblocks later work
    3. Write down what's out of scope so it doesn't creep back in
    4. Revisit the list after the first release, with real usage data

    Tip: Show a simple way to rank the list and name what you'd leave out on purpose.

  4. 4Data and SQL
    They wrote: “Independently design, build, test, and deploy moderately complex AI agents, skills, dashboards, automations, data pipelines, and integrations that improve team productivity and business outcomes.”

    How would you design a daily pipeline that feeds customer data into our product?

    How to answer

    Why they ask: Tests basic data engineering: scheduling, failures, re-runs and monitoring.

    1. Extract with timestamps or change tracking, not full dumps, when possible
    2. Transform in steps you can re-run without creating duplicates
    3. Validate row counts and key fields before loading
    4. Alert a person on failure, with enough detail to fix it

    Tip: Make re-running safe (same input, same result) and say how you'd know it failed.

  5. 5LLMs, RAG and agents
    They wrote: “Respond promptly to production incidents or on-call issues, including troubleshooting and resolving critical disruptions to minimize downtime and business impact.”

    When would you fine-tune a model, and when is prompting or retrieval enough?

    How to answer

    Why they ask: Customers often ask for fine-tuning first. They want to hear you pick the cheapest thing that works.

    1. Try clear prompts and examples first; measure against a test set
    2. If the model lacks the customer's facts, add retrieval
    3. Fine-tune when you need a format or behaviour prompts can't hold, and you have good examples
    4. Count the cost: training data, upkeep and re-testing on every model update

    Tip: Start from what's wrong: missing knowledge points to retrieval, wrong style or format points to fine-tuning.

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Alkami Technology

$128–160k · Remote

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