Senior Value Engineer - Banking

Celonis•New York, NY

1d•$131,250 - $153,750•Hybrid

About The Position

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet. As a Senior Value Engineer specializing in Banking, you are at the forefront of solving business-critical problems for some of the world's largest financial institutions. You will work intimately with strategic enterprise clients to understand their complex objectives—ranging from accelerating Loan Origination and Client Onboarding to optimizing Capital Markets Operations and Regulatory Reporting. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners. By feeding operational context to AI, you help banks understand the intricate realities of their massive transactional ecosystems. You will prototype these solutions, demonstrate their value to Banking Executives (COOs, CROs, and Heads of Digital Transformation), and ensure successful implementation and value realization to solidify and expand the Celonis footprint across the global financial landscape.

Requirements

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: 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.
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.

Nice To Haves

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).

Responsibilities

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.