Help build the backend, artificial intelligence, and machine-learning foundations that power Socure’s agentic investigation systems, focusing on backend services, distributed systems, AI agents, retrieval, and ML models.
Responsibilities
Design, implement, test, and operate backend services that support agent orchestration, task execution, state management, model integrations, and investigation workflows.
Build synchronous and asynchronous workflows for agent tasks, including queues, retries, resumability, cancellation, idempotency, scheduling, and failure recovery.
Contribute to agent frameworks and developer harnesses that support tool calling, structured outputs, reusable skills, actor-based workflows, human review, and policy-controlled execution.
Implement services that dynamically inject relevant knowledge into agent workflows based on investigation type, entity context, workflow state, customer policy, prior findings, and current task requirements.
Build domain-grounding capabilities that help agents distinguish authoritative facts, customer-defined policies, derived signals, hypotheses, and unverified observations.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related technical field
Master’s degree in Computer Science, Engineering, or a related technical field
Nice to have: AI or machine-learning systems for fraud
Nice to have: AI or machine-learning systems for identity
Nice to have: AI or machine-learning systems for financial crime
Software Engineer – Backend Platforms and Agentic & ML Systems to help build the backend, artificial intelligence, and machine-learning foundations that power Socure’s agentic investigation systems.
Responsibilities
Design, implement, test, and operate backend services that support agent orchestration, task execution, state management, model integrations, and investigation workflows.
Build synchronous and asynchronous workflows for agent tasks, including queues, retries, resumability, cancellation, idempotency, scheduling, and failure recovery.
Contribute to agent frameworks and developer harnesses that support tool calling, structured outputs, reusable skills, actor-based workflows, human review, and policy-controlled execution.
Implement services that dynamically inject relevant knowledge into agent workflows based on investigation type, entity context, workflow state, customer policy, prior findings, and current task requirements.
Build domain-grounding capabilities that help agents distinguish authoritative facts, customer-defined policies, derived signals, hypotheses, and unverified observations.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related technical field
Master’s degree in Computer Science, Engineering, or a related technical field
Nice to have: AI or machine-learning systems for fraud
Nice to have: AI or machine-learning systems for identity
Lead AI data security assessments, architecture workshops, and implementation programs for generative AI and agentic systems, translating business and risk objectives into target architectures and guiding teams from assessment through production adoption.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. A reasonable estimate of the current range is $134,500 to $265,100. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
Lead AI data security assessments and architecture workshops
Translate data use cases and risk requirements into target architectures
Involve in design reviews, entitlement and metadata decisions
Manage engagement scope, teams, milestones, quality, and client expectations
Coordinate data security dependencies across identity, cloud, network, AI engineering, application security, privacy, and operations teams
Requirements
Bachelor’s Degree in Computer Science, Engineering, Information Technology, Cybersecurity or a related field
Nice to have: Managed AI services
Nice to have: self-hosted AI platforms
Nice to have: AI threat modeling
Nice to have: red teaming
V
Applied AI Engineer – GenAI Platform (Credit Complex)
Cyber Manager: AI Data SecurityDeloitte · Atlanta, US