Forward Deployed Engineer

FORWARD DEPLOYED ENGINEER

At Oscilar, we’re building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage fraud, credit, and compliance risk with the power of AI. If you’re passionate about solving complex problems and making the internet safer for everyone, this is your place.

WHY JOIN US?

• Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, united by a shared goal to make the digital world safer.
• Ownership and impact: We believe in extreme ownership. You’ll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.
• Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.

ROLE OVERVIEW

The Forward Deployed Engineer (FDE) is a deeply technical, customer-facing role at Oscilar. You sit at the intersection of customer success, platform expertise, and agentic AI deployment. From the first technical conversation with a prospective customer through production deployment and ongoing expansion, you own the full technical relationship.

You’ll be embedded with Oscilar’s most strategic customers, designing agentic risk systems, driving implementations, and translating insights from the field into improvements to our platform.

You’ll operate with the ownership and judgment of a startup CTO, applied to some of the most consequential risk decisioning problems in financial services.

WHAT YOU’LL DO

TECHNICAL PRE-SALES

• Lead technical discovery with prospective customers, uncovering integration requirements, data architecture constraints, and risk decisioning objectives across onboarding, fraud, credit, and compliance use cases.
• Architect and deliver proof-of-concept implementations using Oscilar’s platform, translating customer challenges into workflows and agentic solutions that demonstrate clear value and fast time-to-value.
• Design and present solution architectures tailored to each prospect’s environment, including API integration patterns, data pipeline design, and agent workflow configuration.
• Contribute to technical sections of RFPs, security questionnaires, and integration feasibility assessments.
• Serve as the primary technical voice during evaluations, building credibility and trust with customer engineering, data, and risk teams.

CUSTOMER IMPLEMENTATION & DEPLOYMENT

• Own end-to-end technical implementations for new customers, partnering with the Technical Account Manager, Account Executive, and Sales Engineer from kickoff through go-live, including integration design, data mapping, agent workflow configuration, and user acceptance testing.
• Configure and optimize Oscilar’s AI agents and decisioning rules to match each customer’s operational context, risk appetite, and regulatory environment.
• Use AI coding tools such as Claude, Codex, and Cursor to rapidly prototype scripts, build workflow automations, parse logs, and debug integrations.
• Serve as the primary technical point of contact for assigned accounts throughout the customer lifecycle, building trusted advisor relationships with technical practitioners and executive stakeholders.
• Lead technical health reviews, proactively identify performance gaps, and drive escalations to resolution with urgency and clear ownership.
• Identify expansion opportunities by connecting customer workflow gaps to underused Oscilar capabilities. Partner with the Account Executive to develop concrete, technically grounded proposals.
• Lead technical enablement sessions and training so customer teams can confidently and independently operate Oscilar’s agentic platform.

AGENTIC AI DEPLOYMENT

• Design and deploy multi-step agentic workflows that automate onboarding, fraud investigation, credit decisioning, case management, alert triage, and compliance monitoring.
• Configure agent parameters directly through Oscilar’s UI, including field mappings, matching thresholds, and disposition policies tailored to each customer’s operational context.
• Evaluate customer data infrastructure, model outputs, and decisioning logic to improve agent performance and reliability in production.
• Craft and refine LLM prompts within agent workflows to support accurate, auditable, and compliant behavior.
• Participate in agent backtesting, running configuration changes against historical case data to validate performance before production deployment.
• Guide customers in defining their agentic AI strategy for risk operations, including which decisions to automate, how to structure human-in-the-loop oversight, and how to measure effectiveness.
• Apply and communicate agent evaluation concepts, including evals, golden datasets, and false-positive feedback loops.
• Stay current on agentic AI patterns, tooling, and best practices, and bring that expertise into customer strategy conversations.

PRODUCT INTELLIGENCE

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