Forward Deployed Engineer - RiskOS Agents
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.
About the job
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.
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
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