Vice President – AI Implementation & Financial Technology

Company DescriptionPalmer Square Capital Management LLC, founded in 2009, is a boutique investment manager based near Kansas City specializing in corporate credit and structured credit. Currently managing approximately $36.0 billion (as of 3/31/2026), the firm serves a diverse clientele, including institutions, family offices, and registered investment advisory firms. The investment team is composed of professionals with extensive experience in credit, alternatives, equity, and risk management. Known for its opportunistic and strategic approach, Palmer Square is committed to delivering innovative solutions to achieve client goals. For more information, visit www.palmersquarecap.com.As the firm continues to grow its platform and deepen its analytical capabilities, Palmer Square is investing in next-generation tools and talent at the intersection of finance and technology. This role reflects that commitment.Role DescriptionWe are seeking an intellectually curious, hands-on technologist and finance professional to lead the practical implementation of AI across Palmer Square's investment and operational functions. This is a high-impact, highly visible role for someone who can bridge the worlds of asset management and applied AI — identifying where automation and machine intelligence create genuine leverage, and then building and deploying those solutions. The right candidate is as comfortable speaking with portfolio managers about investment workflows as they are writing Python or crafting LLM prompts.ResponsibilitiesAI Strategy & ImplementationServe as the firm's internal champion and practitioner for AI adoption, identifying high-value use cases across investment, research, risk, operations, and client reportingBuild, test, and deploy AI-powered tools and workflows using large language models (LLMs), AI coding assistants, and automation frameworksDevelop and maintain a roadmap for AI implementation across the firm, balancing quick wins with longer-term infrastructure investmentsEvaluate and manage relationships with AI vendors, data providers, and technology partnersInvestment & Research ApplicationsBuild AI-assisted models for credit analysis, portfolio construction, scenario analysis, and risk monitoring across CLOs, leveraged loans, and other credit strategiesAutomate ingestion and parsing of unstructured data sources — trustee reports, offering memoranda, earnings transcripts, news flow — using LLM-based extraction pipelinesDevelop tools that surface relevant market intelligence, monitor portfolio positions, and flag anomalies with reduced manual effortOperations & Workflow AutomationIdentify and eliminate manual, repetitive workflows across middle and back office functions including compliance, investor reporting, and trade operationsBuild internal AI assistants or co-pilots tailored to firm-specific knowledge bases, policies, and dataPartner with IT, compliance, and operations teams to ensure AI tools meet data security, auditability, and regulatory requirementsEnablement & CultureTrain and upskill investment and operations staff on effective use of AI tools, including prompt engineering best practicesCreate documentation, templates, and reusable frameworks that allow non-technical colleagues to leverage AI in their daily workflowsFoster a culture of experimentation — running structured pilots, measuring outcomes, and scaling what worksQualificationsRequired3+ years of experience in asset management, financial services, or a closely adjacent fieldDemonstrated, hands-on experience building with AI tools — LLM APIs, AI coding assistants, or workflow automation platforms — not just familiarity or enthusiasmProficiency in Python and comfort in a code-first environment; ability to build and ship working tools, not just prototypesStrong understanding of investment management workflows across the front, middle, and back officeExcellent communication skills; able to translate between technical and non-technical stakeholders at all levels of the organizationPreferredExperience in structured credit, CLOs, leveraged loans, or alternative asset managementFamiliarity with LLM APIs (OpenAI, Anthropic) and agentic frameworks such as LangChain, LangGraph, LlamaIndex, or similarExperience applying ML techniques (clustering, NLP/sentiment, supervised models, OCR, transcription) to financial data, document ingestion, or research automationBackground in data engineering, quantitative analysis, or financial systems integration; familiarity with tools such as SQL, vector databases, Spark, Airflow, Kafka, or Docker/Kubernetes a plusExperience with relevant data sources including Bloomberg, Intex, Trepp, or loan data vendorsPrior experience leading technology change management or innovation initiatives at a financial firm