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Ai Risk Analyst Jobs in Lancaster, SC (NOW HIRING)

AVP, Digital Enablement

Fort Mill, SC · On-site

$104K - $174K/yr

... model risk management, or regulatory operations. * Bachelor's degree in Business, Finance, Data Analytics, or a related field required. * Experience supporting or managing analytical or AI model ...

... risk management, or regulatory operations. * Bachelor's degree in Business, Finance, Data Analytics, or a related field required. * Demonstrated experience supporting or managing analytical or AI ...

Enterprise Intern

Charlotte, NC · Hybrid

$15.75 - $20.25/hr

Use AI tools such as Microsoft Copilot to summarize documents, extract key information, and support ... Data Analytics, or a related field. * Strong attention to detail and organizational skills.

Showing results 21-40

Ai Risk Analyst information

See Lancaster, SC salary details

$13

$34

$56

How much do ai risk analyst jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for ai risk analyst in Lancaster, SC is $34.53, according to ZipRecruiter salary data. Most workers in this role earn between $25.43 and $42.02 per hour, depending on experience, location, and employer.

How does an AI risk analyst collaborate with cross-functional teams to assess and mitigate risks?

AI Risk Analysts work closely with data scientists, engineers, compliance officers, and business leaders to identify, evaluate, and mitigate risks associated with AI systems. They facilitate risk assessment workshops, gather input from technical and non-technical stakeholders, and ensure that risk controls are integrated into AI development processes. Effective communication and documentation are crucial, as analysts must translate complex technical risks into actionable recommendations for diverse teams. This collaborative approach helps ensure that AI solutions are both innovative and aligned with regulatory and ethical standards.

What is the difference between Ai Risk Analyst vs Data Scientist?

AspectAi Risk AnalystData Scientist
Required CredentialsBachelor's in Risk Management, Data Science, or related fields; certifications in AI or risk analysisBachelor's or Master's in Data Science, Statistics, or Computer Science; certifications in data analysis or machine learning
Work EnvironmentFinancial institutions, insurance companies, or tech firms focusing on risk assessmentTech companies, research labs, or any industry leveraging data for insights
Employer & Industry UsagePrimarily in finance, insurance, and risk-focused sectorsAcross various industries including tech, healthcare, finance, and marketing

The main difference is that an Ai Risk Analyst specializes in assessing and managing risks related to AI systems, often within financial or risk-focused industries. In contrast, a Data Scientist analyzes large datasets to extract insights across diverse sectors. While both roles require strong analytical skills and knowledge of AI and data tools, the Ai Risk Analyst focuses more on risk mitigation specific to AI applications.

What skills and qualifications are needed to be an AI risk analyst?

To thrive as an AI Risk Analyst, you need a strong foundation in data analysis, risk assessment, and an understanding of AI/ML technologies, typically supported by a degree in computer science, statistics, or a related field. Familiarity with risk management frameworks, AI auditing tools, and certifications such as CRISC or AI ethics credentials is often required. Excellent problem-solving, critical thinking, and communication skills help in identifying risks and conveying complex findings to stakeholders. These skills are crucial to ensure responsible AI deployment, mitigate potential risks, and maintain regulatory compliance.

What is an AI risk analyst?

AI Risk Analysts are professionals who assess, monitor, and manage the risks associated with the development and deployment of artificial intelligence systems. Their work involves identifying potential threats such as bias, security vulnerabilities, ethical concerns, and compliance issues that could arise from using AI technologies. They collaborate with data scientists, engineers, and compliance teams to develop risk mitigation strategies and ensure that AI systems operate safely, ethically, and in accordance with relevant regulations.
What cities near Lancaster, SC are hiring for Ai Risk Analyst jobs? Cities near Lancaster, SC with the most Ai Risk Analyst job openings:

Sr AI Platform Engineer - Agent Integration & Tool

LPL Financial Holdings, Inc.

Fort Mill, SC • On-site

Other

Medical, Retirement, PTO

Re-posted 8 days ago


LPL Financial rating

7.5

Company rating: 7.5 out of 10

Based on 70 frontline employees who took The Breakroom Quiz

116th of 150 rated financial services


Job description

Where Ambition Meets Innovation
Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you'll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals.
Job Overview:
The Senior Engineer, Agent Integration & Tool Platform is responsible for designing and operating the enterprise platform that enables secure, governed, and reusable integration between AI agents, enterprise systems, APIs, applications, data products, and external services.
This role will establish the standards, frameworks, and platform capabilities that allow development teams to rapidly onboard tools and services while maintaining enterprise requirements for security, governance, resiliency, observability, and auditability.
The ideal candidate combines deep expertise in distributed systems, API architectures, platform engineering, and emerging agent interoperability standards to create a scalable foundation for enterprise AI ecosystems.
Responsibilities
Agent Integration Platform
  • Design and implement enterprise capabilities that enable AI agents to securely interact with enterprise systems, APIs, applications, and services.
  • Establish reusable integration patterns that accelerate adoption while reducing implementation complexity for development teams.
  • Define enterprise standards for agent interoperability and service integration.

Tool Registry & Discovery Services
  • Build and operate centralized capabilities for tool registration, discovery, metadata management, and lifecycle governance.
  • Establish standards for tool contracts, schemas, versioning, ownership, and operational support.
  • Develop mechanisms that enable agents and applications to discover and consume approved enterprise capabilities.

Agent-to-Agent Communication
  • Define patterns and standards for communication and collaboration between autonomous and semi-autonomous systems.
  • Design mechanisms for agent capability discovery, delegation, orchestration, and coordination.
  • Establish governance and observability frameworks for multi-agent environments.

Platform Governance & Controls
  • Implement controls supporting authentication, authorization, entitlement management, and policy enforcement.
  • Partner with Information Security, Risk, Compliance, and Enterprise Architecture teams to ensure integrations comply with enterprise standards.
  • Ensure all platform capabilities support auditability, traceability, and regulatory requirements.

Developer Enablement
  • Create SDKs, templates, onboarding frameworks, and reference implementations that simplify adoption.
  • Establish engineering standards and best practices for tool integration and agent development.
  • Improve developer productivity through automation, self-service capabilities, and platform abstractions.

Platform Operations & Observability
  • Build capabilities supporting monitoring, tracing, usage analytics, performance management, and operational governance.
  • Establish metrics for tool adoption, reliability, utilization, and business impact.
  • Ensure platform resiliency, scalability, and operational excellence.

Technical Leadership
  • Lead architecture reviews and engineering design decisions.
  • Mentor engineers and influence technical direction across multiple teams.
  • Drive engineering excellence through best practices, reusable patterns, and platform modernization initiatives.

Success Measures
  • Reduction in time required to onboard new tools and enterprise capabilities.
  • Increased reuse of enterprise services across applications and AI systems.
  • Consistent implementation of governance and security controls across integrations.
  • High platform reliability, observability, and operational maturity.
  • Accelerated adoption of agent-based capabilities across the enterprise.

What are we looking for?
We're looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.
Requirements:
  • Minimum of 8 years of software engineering experience.
  • Experience designing and building enterprise integration platforms, API platforms, or distributed systems.
  • Knowledge of API architecture, service contracts, event-driven systems, and platform engineering principles.
  • Experience implementing authentication, authorization, and governance controls in enterprise environments.
  • Experience building developer platforms, SDKs, shared services, or integration frameworks.

Core Competencies:
  • Designs and enables AI agent-to-tool communication frameworks, including tool discovery, service orchestration, and integration patterns that allow agents to securely access APIs, data sources, and enterprise services at scale.
  • Understanding of cloud-native architectures and modern software engineering practices.

Preferences:
  • Experience with agent frameworks, agent orchestration, or autonomous systems
  • Experience with Model Context Protocol (MCP), tool registries, service catalogs, or capability management platforms.
  • Experience with enterprise API management, service mesh, or integration platforms.
  • Familiarity with AI and machine learning platforms and their integration requirements.
  • Experience operating in highly regulated environments.

Pay Range:
$115,154.00 - $191,889.00
Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play - such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!
Company Overview:
LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace(6) , LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans. The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses. For further information about LPL, please visit ;br>
At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.
For further information about LPL, please visit ;br>
Join the LPL team and help us make a difference by turning life's aspirations into financial realities. Please log in or create an account to apply to this position. Principals only. EOE.
Information on Interviews:
LPL will only communicate with a job applicant directly from an @lplfinancial.com email address and will never conduct an interview online or in a chatroom forum. During an interview, LPL will not request any form of payment from the applicant, or information regarding an applicant's bank or credit card. Should you have any questions regarding the application process, please contact LPL's Human Resources Solutions Center at .
EAC 5.19.26

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