Forward Deployed Engineer - CFA

Baker Hill Solutions•Carmel, IN

6d•Onsite

About The Position

Baker Hill is hiring a Forward Deployed Engineer for its next-generation Cash Flow Analysis (CFA) product. This role combines credit analysis expertise with hands-on technical skill to understand how banks and credit unions spread and analyze C&I and complex CRE lending, and to turn those workflows into working AI-powered software. The engineer will embed with customers and design partners, build and deploy solutions using real documents and customer environments, and bring field learnings back to product and engineering teams. The role owns technical delivery for pilots and design partner implementations, from kickoff through production, including data mapping, integrations, and customer enablement. It also supports sales and client success with demos and proofs of concept, and serves as a customer-informed contributor to product roadmaps. Candidates near the Carmel HC office are expected to work onsite and should expect extensive travel to client sites, including a commitment to 50% travel.

Requirements

BA/BS in Finance, Lending Operations, Business, Computer Science, Information Systems, or a related field.
At least 5 years of hands-on experience spreading financial statements and performing cash flow analysis in a bank, credit union, lending environment, or fintech role directly supporting those workflows.
Demonstrated specialization in both C&I and complex CRE underwriting.
Strong working knowledge of business and personal financial statements, tax returns, and cash flow methodologies, including UCA, EBITDA-based analysis, global cash flow, DSCR, and NOI-based CRE analysis.
Proficiency in at least one programming language, with Python preferred, and comfort with SQL, APIs, JSON, and scripting for data transformation and integration.
Experience building or deploying software solutions in customer environments, such as implementation engineering, solutions engineering, or technical consulting.
Strong communication skills with bankers and engineers, including the ability to explain technical tradeoffs to a chief credit officer.
Willingness and ability to travel to customer sites 50%.
Complete a one-hour SAFe overview within the first 90 days of employment.
Use AI responsibly and in alignment with policy, including ongoing learning and incorporating AI into routine tasks.

Nice To Haves

Hands-on experience with LLMs, prompt engineering, retrieval, intelligent document processing, or ML evaluation.
Experience with spreading software or loan origination and credit analysis platforms.
Familiarity with bank security, data privacy, and model risk management requirements.
Background in construction lending, SBA lending, or credit risk review.
Experience in fintech or banking software.
Formal credit training, such as RMA or credit analyst programs.
A recognized AI or AI platform fundamentals credential, or willingness to complete one within the first year of employment.

Responsibilities

Embed with bank and credit union credit teams to observe, document, and improve financial spreading, statement normalization, and calculation of DSCR, global cash flow, and NOI-based metrics.
Build, configure, deploy, and tune AI-assisted workflows for document extraction, statement classification, spreading, adjustments, and narrative generation using real customer data.
Rapidly prototype field solutions such as extraction pipelines, spreading templates, validation rules, and integrations, then transfer proven solutions to product and engineering for productization.
Own technical delivery for pilots and design partner implementations from kickoff through production, including data mapping, integrations with origination and core systems, and customer enablement.
Apply C&I expertise, including working capital and borrowing base analysis, EBITDA normalization and add-backs, covenant testing, seasonality, concentration risk, and multi-entity operating companies.
Apply complex CRE expertise, including rent roll and T-12 analysis, NOI normalization, stabilized and as-is underwriting, lease rollover and tenant concentration, construction and lease-up projections, property types, and global cash flow across sponsor and guarantor portfolios.
Build evaluation harnesses to measure accuracy, explainability, and auditability against analyst-spread benchmarks, and report results to customers and internal teams.
Identify edge cases and convert them into test sets, feedback for the AI team, and product requirements.
Represent the customer in roadmap discussions using evidence gathered in the field.
Support sales and client success with technical demos, proofs of concept, and credibility with credit officers and executives.
Stay current on credit policy, regulatory expectations, model risk management guidance, and competitive offerings.
Use AI responsibly in alignment with policy, model the organization's AI standard, help colleagues meet it, and surface policy questions and risks.