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Embedded Finance Jobs in Alaska (NOW HIRING)

... Workplaces in Financial Services & Insurance VP Responsible AI ESSENTIAL FUNCTIONS and ... Ensure governance controls are embedded directly into AI development, CI/CD, deployment, monitoring ...

... Workplaces in Financial Services & Insurance VP Responsible AI ESSENTIAL FUNCTIONS and ... Ensure governance controls are embedded directly into AI development, CI/CD, deployment, monitoring ...

Principal Software Engineer

Homer, AK · On-site

$140K - $188K/yr

... are embedded from day one. Through technical leadership, collaboration, and example, you will ... financial impact) and make recommendations to the organization. Build the business case for new ...

Embedded Finance information

What are some common challenges professionals face when working in embedded finance roles?

Professionals in Embedded Finance often navigate challenges such as integrating financial services seamlessly into non-financial platforms, ensuring compliance with complex regulations, and maintaining robust data security. Collaboration across teams—like product, engineering, and compliance—is essential to deliver a smooth user experience while adhering to legal standards. Staying current with evolving fintech trends and regulatory changes is also key, as these can significantly impact product development and timelines.

What is embedded finance?

Embedded finance refers to the integration of financial services such as payments, lending, insurance, or investments into non-financial platforms or products. This means that companies outside of traditional banking can offer financial services directly to their customers through their own apps or websites. Examples include ride-sharing apps that offer in-app payments, e-commerce sites providing 'buy now, pay later' options, or retail brands offering branded credit cards. Embedded finance streamlines the customer experience by making financial transactions seamless and convenient within everyday digital interactions.

What are the key skills and qualifications needed to thrive as an embedded finance professional?

To thrive in Embedded Finance, you need a strong background in finance, fintech, and software development, often supported by degrees in finance, computer science, or related fields. Familiarity with APIs, payment processing platforms, compliance systems, and certifications such as CFA or relevant fintech credentials is highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication are essential soft skills for integrating financial solutions across industries. These competencies are crucial to ensure secure, innovative, and seamless financial services within non-financial platforms.

What is the difference between Embedded Finance vs Payment Specialist?

AspectEmbedded FinancePayment Specialist
CredentialsFinancial certifications, fintech knowledgeFinancial or technical certifications, payment systems expertise
Work EnvironmentFintech companies, banks, tech firms integrating financial servicesPayment processing companies, banks, e-commerce platforms
Industry UsageDeveloping embedded financial products within platformsManaging and optimizing payment systems and transactions

Embedded Finance involves integrating financial services directly into non-financial platforms, focusing on product development and user experience. Payment Specialists primarily manage and optimize payment processes and systems. While both roles require financial and technical knowledge, Embedded Finance professionals focus on creating seamless financial integrations, whereas Payment Specialists concentrate on transaction efficiency and security.

What are popular job titles related to Embedded Finance jobs in Alaska? For Embedded Finance jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Embedded Finance jobs in Alaska look for? The top searched job categories for Embedded Finance jobs in Alaska are:

Full-time

Posted 7 days ago


Sedgwick rating

7.6

Company rating: 7.6 out of 10

Based on 321 frontline employees who took The Breakroom Quiz

208th of 304 rated insurance


Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work

Fortune Best Workplaces in Financial Services & Insurance

VP Responsible AI

ESSENTIAL FUNCTIONS and RESPONSIBILITIES

Own Sedgwick's enterprise Responsible AI and AI Governance strategy, operating model, roadmap, and maturity evolution.

Serve as the executive business owner for the credo governance platform, including vendor relationship management, platform adoption, workflow design, risk frameworks, controls, reporting, audits, renewals, and strategic direction.

Serve as the executive business owner for the OpenLayer platform, including observability, evaluation, testing, runtime guardrails, monitoring, model quality oversight, and operational governance capabilities.

Own executive relationships with Credo AI and OpenLayer leadership teams and drive product roadmap alignment to Sedgwick requirements.

Establish and maintain Sedgwick's Responsible AI framework using industry standards, regulations, and internal policies.

Own the enterprise AI inventory, use-case registry, model registry, agent registry, and AI risk register.

Define AI risk-tiering methodologies and approval requirements for models, agents, copilots, automation workflows, and third-party AI products.

Design and operate a highly automated AI governance process that minimizes manual reviews while maintaining appropriate controls, auditability, and risk oversight. The workflow includes automated intake, risk classification, policy assignment, routing, control selection, approvals, monitoring, and evidence generation.

Lead the transformation from committee-driven approvals to policy-driven governance with automated controls and risk-based escalation paths.

Ensure governance controls are embedded directly into AI development, CI/CD, deployment, monitoring, and operational processes.

Establish governance requirements for AI systems built internally, acquired through vendors, embedded in third-party applications, or inherited through acquisitions.

Partner with Legal, Compliance, Privacy, Risk, Security, Internal Audit, and Technology leadership to maintain governance alignment.

AI Risk, Compliance & Assurance (close partnership with Sedgwick Privacy Compliance and Cyber Security organization)

  • Establish and maintain AI control frameworks aligned to emerging AI regulations, industry standards, client obligations, and enterprise risk requirements.

  • Own AI compliance evidence, audit readiness, control testing, and governance reporting.

  • Ensure governance controls address bias, privacy, explainability, transparency, security, robustness, hallucination risk, model drift, and human oversight requirements.

  • Define governance requirements for vendor AI products, foundation models, copilots, agents, and autonomous workflows.

  • Lead management of AI incidents, exceptions, waivers, and remediation programs.

  • Develop governance KPIs, KRIs, scorecards, and executive dashboards.

OpenLayer & Operational Governance Oversight

  • Ensure pre-deployment evaluations are executed for quality, risk, robustness, hallucination, toxicity, and compliance requirements.

  • Oversee runtime monitoring for drift, policy violations, security threats, model degradation, and operational risk.

  • Ensure continuous monitoring evidence is captured and routed into governance reporting and audit processes.

  • Establish closed-loop governance processes that convert production issues into improved controls, policies, evaluations, and testing requirements.

Leadership Expectations

  • Build and lead a cross-functional Responsible AI, AI Governance

  • Chair or co-chair enterprise AI Governance councils and executive committees.

  • Influence executive leadership, regulators, clients, auditors, and technology partners on Responsible AI strategy.

  • Act as Sedgwick's senior authority on Responsible AI, AI Governance, and AI risk management.

  • Drive a culture that enables rapid AI innovation while maintaining trust, transparency, compliance, security, and accountability across the enterprise.

Success Measures

  • Percentage of AI use cases governed through automated workflows.

  • Policy compliance across AI systems and vendors.

  • Audit and regulatory readiness scores.

  • Reduction in governance cycle time.

  • AI inventory and registration completeness.

  • Number of AI systems continuously monitored through OpenLayer.

  • Data quality and lineage coverage across AI workloads.

  • Reduction in manual governance reviews through risk-based automation.

  • Executive and client confidence in Sedgwick's Responsible AI program.

SUPERVISORY RESPONSIBILITIES

  • Provides strategic leadership, direction, coaching, and development to Responsible AI, AI Governance, and related governance program teams.

  • Builds, leads, and develops a high-performing organization focused on AI governance, risk management, compliance, controls, oversight, and operational excellence.

  • Establishes organizational objectives, performance expectations, talent development plans, succession strategies, and resource allocation priorities.

  • Oversees recruitment, selection, onboarding, performance management, and professional development of team members.

QUALIFICATIONS


Bachelor's degree in Computer Science, AI or Data Engineering. A Master's degree is preferred.

  • Fifteen (15) years of progressive leadership experience in computer science, artificial intelligence, data engineering, technology governance, risk management, compliance, or a related field.

  • Significant experience leading enterprise-scale AI governance, responsible AI, model risk management, data governance, technology risk, or digital transformation programs.

  • Demonstrated experience developing and operationalizing governance frameworks, control models, risk-tiering methodologies, policy standards, approval workflows, and compliance monitoring processes.

  • Experience working with AI/ML systems, generative AI, foundation models, copilots, agents, automation workflows, model registries, AI inventories, and third-party AI products.

  • Experience implementing or overseeing governance, risk, compliance, observability, model monitoring, model evaluation, or AI control platforms.

  • Proven ability to partner with Legal, Compliance, Privacy, Risk, Security, Internal Audit, Technology, Data, and business leadership to align governance requirements across the enterprise.

  • Experience preparing for audits, regulatory reviews, client inquiries, control testing, evidence collection, governance reporting, and executive-level risk reviews.

  • Demonstrated experience leading cross-functional teams, executive governance councils, committees, or enterprise-wide transformation initiatives.

  • Experience managing vendor relationships, technology platforms, product roadmaps, contract renewals, and strategic partnerships preferred.

  • Experience in a highly regulated industry or complex global enterprise environment preferred.

Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

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