Forward Deployed Engineer II

Ascent Developer Solutions•Encino, CA

4d•Hybrid

About The Position

Ascent Developer Solutions is hiring a Forward Deployed Engineer to build software for complex real estate lending workflows. The engineer embeds with business teams to understand their workflows and develops AI-powered tools that help scale their expertise. This is an engineering-first role involving production code, security review, and post-launch support. The position reports directly to the Head of Technology, with scope growing as projects are delivered. The engineer partners with business teams and Platform Engineering to map workflows, identify and prioritize automation opportunities, develop specifications, and build production automations using Python or TypeScript, APIs, and LLM-based agents. Automations must work within the existing platform and meet security and AI governance requirements, including sandboxed development, least-privilege access, audit logging, human review where loan decisions may be affected, and independent security review before production. The role also measures automation results, trains users, supports adoption, maintains documentation and runbooks, and partners with Data & Analytics. The position is based at Ascent’s Encino office Monday through Thursday, with Fridays worked from home. Salary is up to $130,000 per year, with a discretionary annual bonus of 15%.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
3–5 years of professional software engineering experience, including experience with systems relied on daily by non-technical business users.
Production experience with Python or TypeScript, SQL, and REST API integrations.
Hands-on experience shipping LLM-based features to production, including tool use, structured outputs, document extraction, retrieval, and evaluation.
Daily use of AI coding tools, with the discipline to review and test their output.
Experience designing agent loops that act, check results against clear goals, and stop or hand off to a person at the appropriate point.
Ability to conduct discovery with business users and translate findings into clear process maps and specifications.
Systems thinking and ability to design for the whole process rather than only an individual task.
Sound security practices, including least-privilege access, secrets management, logging, and safe handling of sensitive personal and financial data.
Clear writing and communication skills, including the ability to explain technical tradeoffs to business partners and executives.
High ownership and comfort starting from an incomplete problem statement.

Nice To Haves

Experience with agent frameworks.
Consulting, solutions engineering, internal tools, or business systems experience.
Experience in lending, real estate finance, or another regulated financial services environment.
Experience with OutSystems or another low-code platform, Microsoft 365/SharePoint, and Jira.

Responsibilities

Embed with assigned business teams to understand their systems, documents, decisions, handoffs, and day-to-day work.
Map workflows end to end, including inputs, systems, decision rules, handoffs, exceptions, and upstream and downstream connections; keep the maps current.
Identify and size automation opportunities by hours saved, error reduction, and risk, and agree on priorities with department leadership and the Head of Technology.
Write build-ready specifications for Platform Engineering, including data requirements, business rules, edge cases, and acceptance criteria, and co-ship core lending platform work.
Work with Platform Engineering to ensure automations use the existing platform’s shared data, integrations, identity, and monitoring, and turn recurring patterns into reusable components.
Build and ship production automations across lending workflows using Python or TypeScript, APIs, and LLM-based agents.
Design agent workflows with clear goals, appropriate tools, verification against expected results, defined stop conditions, and human checkpoints when needed.
Take automations through security and AI governance review, including sandboxed development, least-privilege agent identities, audit logging, human review of outputs affecting loan decisions, and independent security review before production.
Measure each automation against a pre-launch baseline and report results.
Drive adoption by training users, updating procedures, and resolving issues promptly after launch.
Monitor and support shipped automations and maintain runbooks for handling exceptions.
Partner with Data & Analytics on data definitions, field-identified data-quality issues, and automation metrics.
Follow engineering standards, including version control, code review, automated testing, and change management.
Protect borrower data in accordance with GLBA, company security policies, and the AI Use Policy, and raise risks early.
Evaluate AI tools and vendors when appropriate and recommend whether to build or buy.
Keep workflow maps, specifications, runbooks, and change logs current to support maintenance and handoff.
Rotate to a new department after the current department’s automations are stable and documented.
Provide regular, clear updates on progress, blockers, and results to department leaders and the Head of Technology.