# Forward Deployed Engineer - RiskOS Agents

**Company:** [Socure](https://hotfix.jobs/companies/socure)
**Location:** San Francisco, CA, Seattle, WA, New York, NY
**Role:** Solutions Architecture
**Salary:** $250k – $280k/yr
**Experience:** 4+ years
**Skills:** Python, SQL, APIs, Cloud Services, Workflow Tools, Llm Workflows, Retrieval Systems, Tool Calling, Evaluation Frameworks, Observability, Agentic Systems, Workflow Orchestration, Case Management, Rules Engines, Decisioning Platforms
**Posted:** 2026-08-17

> Build and deploy AI-assisted RiskOS workflows for strategic customers, owning the path from discovery and technical scoping through production adoption. The role requires 4+ years of hands-on technical experience, customer-facing problem solving, and familiarity with APIs, cloud services, Python, SQL, and agentic or LLM systems.

## Job Description

## Responsibilities
- Work directly with strategic customers and partners to understand workflows, data environments, technical constraints, business goals, and operational pain points.
- Own deployments from prototype to production, including discovery, technical scoping, solution design, building, integration, testing, rollout, and adoption.
- Translate customer policies, SOPs, data sources, and operational processes into RiskOS 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 and improve agentic workflows involving tools, data, evidence, decisions, analyst queues, and business logic through testing, evaluations, observability, guardrails, feedback, and production learnings.
- Measure customer outcomes such as speed, accuracy, consistency, analyst productivity, review burden, evidence quality, and operational control.
- Convert product gaps, implementation friction, and repeatable patterns into reusable templates, playbooks, primitives, and product capabilities with product, engineering, data science, security, and GTM teams.

## Requirements
- Strong hands-on technical ability across APIs, integrations, workflow logic, data mappings, internal tools, scripts, production systems, or cloud services.
- Ability to own ambiguous customer problems from discovery through production.
- Experience solving problems directly with enterprise customers, strategic partners, or internal business stakeholders.
- Product-minded engineering judgment across architecture, implementation, debugging, user needs, product tradeoffs, operational risk, and stakeholder communication.
- Systems thinking, calm execution, high agency, and comfort with ambiguity.
- 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.
- Experience with Python, SQL, APIs, cloud services, workflow tools, LLM workflows, retrieval systems, tool calling, copilots, evaluation frameworks, observability, or agentic systems is helpful.

## Preferred Qualifications
- Experience deploying AI, ML, LLM, or decision-support systems in production.
- Experience in fraud, risk, identity verification, KYC, KYB, AML, sanctions, adverse media, transaction monitoring, disputes, trust and safety, or compliance operations.
- Experience with large financial institutions, government agencies, marketplaces, gaming companies, fintechs, or complex enterprise customers.
- Experience with workflow orchestration, case management, rules engines, decisioning platforms, operational automation, evaluation pipelines, or customer-specific implementation tooling.

## Compensation and Success Measures
- The role offers an annual salary range of **$250000-$280000**.
- By year one, strategic customers and partners are expected to be live or in advanced rollout with AI-assisted RiskOS workflows that deliver measurable operational value.
- Customer-specific learnings should become reusable templates, playbooks, evaluation patterns, workflow primitives, implementation accelerators, or product requirements.

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