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AI Integration Sr. Analyst - Risk AnalyticsTexas Capital Bank • United States
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AI Integration Sr. Analyst - Risk Analytics

Texas Capital Bank
  • US
    United States
  • US
    United States
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Über

Texas Capital is built to help businesses and their leaders. Our depth of knowledge and expertise allows us to bring the best of the big firms at a scale that works for our clients, with highly experienced bankers who truly invest in people's success - today and tomorrow.
While we are rooted in core financial products, we are differentiated by our approach. Our bankers are seasoned financial experts who possess deep experience across a multitude of industries. Equally important, they bring commitment - investing the time and resources to understand our clients' immediate needs, identify market opportunities and meet long-term objectives. At Texas Capital, we do more than build business success. We build long-lasting relationships.
Texas Capital provides a variety of benefits to colleagues, including health insurance coverage, wellness program, fertility and family building aids, life and disability insurance, retirement savings plans with a generous 401K match, paid leave programs, paid holidays, and paid time off (PTO).
Headquartered in Dallas with offices in Austin, Fort Worth, Houston, Richardson, Plano and San Antonio, Texas Capital was recently named Best Regional Bank in 2024 by Bankrate and was named to The Dallas Morning News' Dallas-Fort Worth metroplex Top Workplaces 2023 and GoBankingRate's 2023 list of Best Regional Banks. For more information about joining our team, please visit us at www.texascapitalbank.com.
Overview of the Position
Texas Capital Bank is seeking an experienced AI Integration Senior Analyst to join the Risk and Compliance group. This role is focused on designing, building, and deploying sophisticated AI agents using the bank's enterprise agent-building platform, with a strong emphasis on risk management and compliance workflows. The ideal candidate brings substantial banking and risk/compliance experience combined with advanced AI development expertise, enabling them to serve as a technical leader and trusted advisor to Risk Analytics and the broader Risk Organization.
As an AI Integration Sr. Analyst embedded within Risk Analytics, you will be a technical leader and strategic advisor working closely with the broader Risk and Compliance, and Technology teams to identify transformational opportunities where AI agents can automate, augment, and accelerate workflows. You will lead the design and implementation of sophisticated agent solutions, mentor junior developers and analysts, influence technical strategy, and ensure all deliverables meet stringent regulatory and compliance standards. You will be responsible for designing enterprise-grade agent logic, integrating data sources, testing AI outputs, and ensuring reliability, accuracy, and auditability of deployed agents.
Responsibilities
Lead technical strategy and agent-based workflows, ensuring alignment with enterprise standards and regulatory requirements.
Design and develop production-grade AI agents to support credit risk, portfolio monitoring, compliance reviews, and other mission-critical risk functions.
Collaborate with Risk leadership and domain experts to translate complex credit, compliance, and risk workflows into scalable, auditable AI-powered solutions.
Integrate agents with internal data systems, APIs, and enterprise tools to enable end-to-end automation while maintaining data governance and compliance standards.
Build, test, and iterate on advanced agent logic including prompt engineering, tool use, memory management, and multi-step reasoning flows.
Mentor junior analysts and contribute to internal best practices, documentation, and the AI community of practice.
Own the entire AI agent's lifecycle, providing maintenance, troubleshooting issues, and driving continuous improvements with a focus on accuracy and regulatory compliance.
Stay current with advancements in large language models (LLMs), agentic frameworks, and enterprise AI tooling.
Ensure all agent outputs meet stringent data quality, auditability, and compliance standards required in a highly regulated banking environment.
Support Risk Analytics with dashboards and other data driven solutions aimed at extracting actionable insights.
Contribute to broader AI/ML strategy and help establish governance frameworks for responsible AI deployment.
Qualifications
Bachelor's Degree in Computer Science, Data Science, Data Engineering, Software Engineering, Mathematics, or a related field, or equivalent hands-on experience.
Master's Degree preferred
7+ years of professional experience
3+ years specifically building AI-powered applications, intelligent agents, or LLM-based workflows.
3+ years of experience in banking, financial services, or risk/compliance domain with hands-on exposure to financial risk concepts.
Advanced proficiency in Python and demonstrated expertise building multi-step AI workflows with LLMs - including prompt engineering, tool integration, memory management, agent orchestration patterns, and multi-agent systems.
Proven experience integrating AI systems with APIs, databases, enterprise data platforms, and legacy banking systems.
Deep familiarity with credit risk concepts such as risk ratings, portfolio segmentation, credit review processes, loan underwriting, or compliance/audit frameworks.
Experience as a technical lead in financial services or risk-focused environments.
Deep understanding of prompt engineering, retrieval-augmented generation (RAG), agent tool use patterns, and reasoning frameworks.
Ability to understand, translate, and architect complex business, risk, and compliance workflows into scalable technical agent designs.
Strong analytical and problem-solving skills with the ability to balance innovation with regulatory compliance and risk management.
Experience building evaluation frameworks and benchmark suites to systematically assess agent accuracy, reliability, and robustness, including testing across edge cases, adversarial inputs, and real-world use case variability.
Excellent communication and leadership skills - able to influence technical and non-technical stakeholders, mentor analysts, and drive alignment across teams.
Demonstrated commitment to detail, data accuracy, and quality assurance, especially in regulated or high-stakes environments.
Demonstrated experience designing and implementing Model Context Protocol (MCP) servers to enable secure, structured communication between AI agents and external tools, APIs, and enterprise resources.
Proven ability to build and maintain scalable ETL pipelines that ingest, transform, and deliver data in agent-ready formats, including quality validation, error handling, and automated monitoring.
Solid full-stack engineering skills spanning backend APIs, frontend interfaces, and relational/non-relational databases, with a strong emphasis on clean code practices, automated testing, and CI/CD pipelines.
Hands-on experience with enterprise AI platforms in production environments.
Advanced knowledge of data engineering, SQL, data pipelines, data governance, and cloud platforms (Azure, Snowflake, AWS or similar).
Prior experience mentoring teams or leading cross-functional AI or data-driven initiatives.
The duties listed above are the essential functions, or fundamental duties within the job classification. The essential functions of individual positions within the classification may differ. Texas Capital Bank may assign reasonably related additional duties to individual employees consistent with standard departmental policy.Texas Capital is an Equal Opportunity Employer.
  • United States

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  • English
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