Forward Deployed Engineer (FDE) Engineering Palo Alto

ArcaLabs builds AI agents that perform sell-side tasks (public comps, IC memos, pitchbook strip profiles, earnings comp analysis) end-to-end. We're partnered with some of the largest financial data providers, including FactSet and CapIQ. Our founding team previously built Arcafeed , a SaaS tool for buy-side analysts, which was acquired in late 2025. Our customers are the global heads of M&A, the MDs running pitches, and the analysts who used to spend their nights in Excel. Forward Deployed Engineering is the team that turns research breakthroughs into production systems inside customer environments. We sit at the intersection of customer delivery, product, and core platform work, and we ship workflows that get used the same week we build them. About the role We're hiring a Forward Deployed Engineer (FDE) to lead end-to-end deployments of our agents inside investment banks, asset managers, and private capital firms. You'll fly to a customer's NYC, London, or Hong Kong desk on Monday, sit next to their analysts, and have a working agent running their Monday-morning comps refresh by Friday. Then you'll come back to Palo Alto and roll the patterns you discovered back into the core platform. This is the highest-leverage engineering role at ArcaLabs. You'll build the workflows that define what a sell-side AI analyst can do, in the firm's house style, on FactSet's data, with full audit trails. You'll see the work used live within days. Some of the work you'll do Lead full-cycle deployments at top-tier banks and PE funds: discovery, scoping, building, customer training, and rollout. Build agentic workflows on our own agent runtime, a forked coding-agent CLI that we run in E2B sandboxes and drive from a TypeScript control plane, wired to FactSet data, producing pitch-ready Excel, PowerPoint, and Word deliverables in each firm's house style. Run agent-generated Python inside our E2B sandboxes, with persistent per-deal sessions and WebSocket bridges back to the control plane. Every credentialed tool call is brokered through Hardpan, our Rust secret vault and egress proxy, so the agent process never holds a customer API key. Pair directly with MDs and analysts to model the workflows that matter: the comps templates, IC memo formats, and pitch strip profiles that are version-controlled in their muscle memory. Write production Python and TypeScript against the controls a bank's security review actually asks about: a fail-closed audit trail, encrypted connector tokens, and per-sandbox secret brokering. You'll be the one answering those questions in the room. Land the surfaces bankers already work in: per-environment manifests, Entra app registration, and tenant admin consent for the Excel, Word, and PowerPoint task pane and our Teams bot. Identify reusable patterns across customers and champion them into the core platform with the rest of engineering. You might be a fit if you Have 3+ years of software engineering experience, including time on a customer-facing or platform-applied team (FDE, solutions engineering, or in-house engineering at a fund). Are fluent in Python and TypeScript; have shipped agent-driven features in production: tool loops, sub-agents, streaming, and sandboxed code execution. We don't use an agent framework, so having built and debugged your own model loop counts for more here than any particular SDK. Are comfortable in the Excel/PowerPoint/Word object models: openpyxl, python-pptx, and python-docx for writing, ExcelJS and JSZip for reading OOXML back. You've debugged a corrupt .xlsx, chased down an Excel repair-on-open prompt, or written formula provenance into cell comments. Read a 10-K like a banker reads a pitch deck: fast, with an eye on the footnotes. Are energized by sitting on a trading floor or in a deal room, not behind a Jira board. Have opinions about agent design, evals, retrieval, and tool use, and want to put them into production this quarter. Prior experience inside an investment bank, PE fund, asset manager, or financial data vendor (FactSet, Bloomberg, S&P, Refinitiv). Have deployed an Office add-in or a Teams app into a locked-down enterprise tenant: manifest hosting, Entra registration, admin consent, and AppSource submission. Terraform + AWS (RDS, S3, VPC). Terraform manages our data plane; services deploy from Dockerfiles and agent sandboxes are E2B templates defined in TypeScript. Compensation $180K – $280K + meaningful equity. Full benefits, relocation support, and daily breakfast, coffee, and snacks, plus complimentary fitness center access in Palo Alto. Travel covered to customer sites globally. About ArcaLabs ArcaLabs is the official FactSet AI Partner, building AI agents that run sell-side workflows for investment banks and PE funds. We're the team behind Arcafeed (acquired) and we're hiring the founding squad in Palo Alto. We believe AI will widen, not narrow, the set of people who can do high-end finance work. We want to ship that future. Equal opportunity ArcaLabs is an equal opportunity employer. We hire based on merit, and we accommodate applicants with disabilities. If you need accommodation during the hiring process, email View email address on click.appcast.io . #J-18808-Ljbffr ArcaLabs AI, Inc.