About the role

Senior Software Engineer on Socure's Agentic AI Foundations team designing vendor-agnostic agent platform. Building secure and scalable systems for internal workflows and customer-facing products.

Responsibilities

Design and build a vendor-agnostic agent platform, including orchestration, tool use, memory, and runtime systems that can be reused across multiple workflows and teams.
Develop evaluation and reliability frameworks (metrics, harnesses, pipelines) to measure and improve agent performance, robustness, and safety in production.
Implement safety and governance controls such as guardrails, policy enforcement, and human-in-the-loop review mechanisms to ensure responsible agent behavior and compliance with internal and external standards.
Build systems for data grounding, retrieval, and memory that enable agents to be accurate, context-aware, and aligned with Socure’s domain knowledge and policies.
Prototype, iterate on, and productionize agent behaviors including planning, multi-step execution, and coordination of tools and services, using real internal workflows as proving grounds.
Partner with product and engineering teams across Socure to identify high-impact use cases, jointly design agent-powered workflows, and launch them into production using the platform primitives you build.
Define and document best practices, design patterns, and paved paths for building secure, observable, and scalable agent systems, and mentor other engineers on how to apply them.
Contribute to the team’s strategy and roadmap by informing architecture choices, identifying technical risks, and helping prioritize foundational investments (e.g., tracing, evaluation approaches, dev tooling).

5+ years of professional software engineering experience with a strong background in large-scale distributed systems, backend platforms, or infrastructure.
3+ years of experience designing, building, and operating production-grade systems with clear reliability, performance, and observability requirements.
Hands-on experience with LLMs, Agentic AI systems, or building intelligent applications (e.g., using modern LLM APIs, orchestration frameworks, or ML-powered services in production).
Demonstrated ability to operate in ambiguity and build from first principles in zero-to-one or highly novel problem areas, including making sound trade-offs under uncertainty.
Strong product and systems thinking: you can connect technical decisions to real-world impact, understand user and business needs, and design systems that balance speed, quality, and safety.
Familiarity with AI safety, security, or policy systems such as guardrails, content filtering, access controls, or audit and compliance mechanisms.
Proficiency in at least one modern backend programming language and ecosystem (e.g., Java, Go, Python, or similar) and comfort working with cloud-native infrastructure, APIs, and data services.
Experience collaborating with cross-functional partners (e.g., product, data science, platform, security) to deliver complex technical initiatives.