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Senior Value Engineer - Banking

131k – 154kNew York, NYHybrid5+ YOE
Summary

Senior Value Engineer specializing in Banking who leads technical pre- and post-sales engagements for AI-driven Process Intelligence solutions at major financial institutions. Requires 5+ years in complex Banking/Financial Services environments, deep domain knowledge across lending, capital markets, and regulatory functions, plus technical fluency in Python, SQL, and generative AI techniques.

About the role

Key Responsibilities

AI Discovery & Solutioning

  • Understand clients' overarching AI strategies and distinct challenges in Banking (e.g., fraud detection, credit risk assessment, automating KYC/AML)
  • Translate complex financial workflows into innovative AI solutions that drive measurable ROI

Pre- and Post-Sales Execution

  • Actively drive the customer lifecycle
  • Lead technical discovery and capability demonstrations during the expansion cycle
  • Guide implementation post-sale to ensure efficiency and adoption thresholds are met

Hackathons & Prototyping

  • Tackle heavily siloed legacy core-banking systems
  • Leverage cutting-edge AI to rapidly build prototypes in client hackathons, solving pain points across Settlements, Reconciliations, and Payments

Agentic Process Transformation

  • Support enterprise clients in shifting from rule-based automation to autonomous AI agents
  • Enable "intelligent" banking processes, such as autonomous exception handling in Trade Ops or automated Complaints Management

Proof Projects

  • Execute end-to-end business-critical Proof-of-Value projects
  • Architect secure, scalable LLM/agent systems (with RAG and guardrails) that integrate with complex enterprise stacks like SAP Banking, Salesforce FINS, or core-banking ledgers

Domain Practitioner Leadership

  • Serve as a functional subject matter expert for the Banking value chain
  • Scale knowledge across the organization regarding the nuances of financial operations and transaction lifecycles

Requirements

  • 5+ years of experience leading technical pre-sales and post-sales engagements specifically within complex Banking or Financial Services environments, including building ROI business cases and guiding technical implementations
  • Deep familiarity with the banking value chain, with the ability to translate operational needs into AI use cases across:
    • Lending & Onboarding: Loan Origination, KYC/AML, and Banking & Lending
    • Capital Markets: Sales & Trading Ops, Settlements, Reconciliations, and Custody Services
    • Support & Governance: Finance, Risk & Controls, and Regulatory/Transaction Reporting
  • Knowledge of RAG, prompt engineering, and multi-agent orchestration used to build high-impact use cases (e.g., intelligent compliance assistants or automated data extraction from complex trade documentation)
  • Solid knowledge of Python and common ML/Data libraries (e.g., pandas, LangChain) as well as SQL for handling massive, high-velocity transactional datasets
  • Strong presentation skills to both internal and external stakeholders, from technical whiteboarding with IT to formal demos for Banking Directors
  • Bachelor's Degree required; Master's Degree in Finance, Computer Science, Economics, or Mathematics preferred

Nice to Have

  • Hands-on experience building systems using LLM orchestration and function calling within highly regulated "Data Sovereignty" environments
  • Familiarity with FSI-specific platforms (e.g., nCino, Guidewire, FIS, Fiserv, or Bloomberg)
  • Experience deploying models across major cloud providers (Azure AI, AWS Bedrock, GCP Vertex)
Skills
PythonpandasLangChainSQLRAGLLM orchestrationprompt engineeringmulti-agent orchestrationGenerative AIMachine Learning
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