Senior Value Engineer - Banking

• AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct challenges inherent to Banking (e.g., fraud detection, credit risk assessment, and 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. Remain deeply involved post-sale to guide implementation, ensuring efficiency and adoption thresholds are met. • Hackathons & Prototyping: Think creatively to 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, scaling knowledge across the organization regarding the nuances of financial operations and transaction lifecycles.

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within complex Banking or Financial Services environments. This includes building ROI business cases and guiding technical implementations. • Strong Domain Knowledge: Deep familiarity with the banking value chain, with the ability to translate operational needs into AI use cases across: • Expertise in Generative AI Techniques: 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). • Technical Fluency: Solid knowledge of Python and common ML/Data libraries (e.g., pandas, LangChain) as well as SQL for handling massive, high-velocity transactional datasets. • Communication: Strong presentation skills to both internal and external stakeholders, from technical whiteboarding with IT to formal demos for Banking Directors. • Degree: Bachelor’s Degree required; Master's Degree in Finance, Computer Science, Economics, or Mathematics preferred. • Agentic Systems: Hands-on experience building systems using LLM orchestration and function calling within highly regulated "Data Sovereignty" environments. • Banking Systems: Familiarity with FSI-specific platforms (e.g., nCino, Guidewire, FIS, Fiserv, or Bloomberg). • Cloud Platforms: Experience deploying models across major cloud providers (Azure AI, AWS Bedrock, GCP Vertex). Visa sponsorship is not offered for this role. The base salary range below is for the role in the specified location, based on a Full Time Schedule. Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location. The base salary range below is for the role in New York, based on a Full Time Schedule. $131,250 — $153,750 USD