Forward Deployed Engineer - RiskOS Agents
New
S
SocureFraud and identity
Remote - USAFull-TimeMiddle
Salary$250K - $280K; $250K – $280K • Offers Equity • Offers Bonus
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Job Details
- Experience
- 4+ years of experience
- Required Skills
- PythonSQLRESTful APIs
Requirements
- Bring 4+ years of experience in software engineering, forward deployed engineering, solutions engineering, implementation engineering, applied AI engineering, technical consulting, or a similar hands-on technical role.
- Build practical solutions across APIs, integrations, workflow logic, data mappings, internal tools, scripts, production systems, cloud services, or similar technical surfaces.
- Take ambiguous customer problems from discovery through production, balancing scope, speed, quality, risk, and long-term platform leverage.
- Work directly with enterprise customers, strategic partners, or internal business stakeholders to understand problems, define solutions, and deliver usable outcomes.
- Apply engineering judgment across architecture, implementation, debugging, user needs, product tradeoffs, operational risk, and stakeholder communication.
- Break complex workflows into modular, testable components, identify risks, and maintain clear follow-through in fast-moving environments.
- Experience with Python, SQL, APIs, cloud services, workflow tools, LLM workflows, retrieval systems, tool calling, copilots, evaluation frameworks, observability, or agentic systems is especially helpful.
- Preferred: Experience deploying AI, ML, LLM, or decision-support systems in production.
- Preferred: Experience in fraud, risk, identity verification, KYC, KYB, AML, sanctions, adverse media, transaction monitoring, disputes, trust and safety, or compliance operations.
- Preferred: Experience with complex enterprise customers or workflow orchestration, case management, rules engines, decisioning platforms, operational automation, evaluation pipelines, or implementation tooling.
Responsibilities
- Work with strategic customers and partners to understand workflows, data environments, technical constraints, business goals, and operational pain points.
- Lead discovery, technical scoping, solution design, building, integration, testing, rollout, and adoption for AI-assisted RiskOS workflows.
- Translate customer policies, SOPs, data sources, and operational processes into workflows, integrations, data mappings, tool connections, case flows, and agent behaviors.
- Write code, configure systems, debug issues, and integrate with customer infrastructure, APIs, data sources, security boundaries, analyst tools, and operational systems.
- Define how agents interact with tools, data, evidence, decisions, analyst queues, and business logic; improve workflows through testing, evaluations, observability, guardrails, feedback, and production learnings.
- Measure deployed workflow outcomes, including speed, accuracy, consistency, analyst productivity, review burden, evidence quality, and operational control.
- Identify product gaps, implementation friction, and repeatable patterns, and partner with product, engineering, data science, security, and GTM teams to develop reusable capabilities.
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