Software Engineer II — Agentic AI Foundations

The role

You will design, build, and harden a secure, vendor-agnostic agent platform. You will work on orchestration, tool use, memory, and runtime systems to enable agent-native operations.

What you will do

• Build components of a vendor-agnostic agent platform including orchestration, tool use, memory, and runtime systems.
• Implement evaluation and reliability tooling to measure and improve agent performance, robustness, and safety.
• Help implement safety and governance controls including guardrails, policy enforcement, and human-in-the-loop review mechanisms.
• Build data grounding, retrieval, and memory components.
• Prototype and iterate on agent behaviors including planning, multi-step execution, and coordination of tools and services.
• Partner with product and engineering teams to implement agent-powered workflows.
• Apply and help refine documented best practices and design patterns for secure, observable, and scalable agent systems.
• Bring foundational knowledge of LLMs, GPU computing, and model serving to technical discussions and implementation decisions.

Required qualifications

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Machine Learning/AI, or a related field from top tier institutions, or equivalent practical experience.
• 2+ years of professional software engineering experience in distributed systems, backend platforms, infrastructure, or comparable technical environments.
• Very strong foundational knowledge of large language models and agentic AI systems, including architectures, prompting and orchestration patterns, tool use, and evaluation approaches.
• Strong foundational understanding of GPU computing and model-serving infrastructure, such as CUDA, vLLM, Ollama, LLMLite, TensorRT-LLM, Triton Inference Server, or similar technologies.
• Solid grounding in distributed systems fundamentals, including concurrency, fault tolerance, observability, and performance.
• Proficiency in at least one modern backend programming language and ecosystem, such as Java, Go, Python, or similar.
• Ability to work productively in ambiguous, early-stage problem spaces with guidance from senior engineers.
• A track record of strong technical performance demonstrated through professional impact, research, challenging technical projects, open-source contributions, internships, or other relevant work.
• Strong collaboration and communication skills.

Nice to have

• Experience with multi-agent systems, workflow orchestration, or distributed coordination frameworks.
• Experience building or using agent platforms such as orchestration frameworks, tool registries, or memory systems, or LLM routing, caching, or fine-tuning pipelines.
• Exposure to evaluation frameworks, experimentation platforms, or ML systems.
• Experience with AI safety, security, or policy systems.
• Experience with retrieval systems, knowledge graphs, or data platforms used to ground LLMs and agents in enterprise contexts.
• Demonstrated depth in ML systems or LLM infrastructure.

About the company

Socure is building the identity trust infrastructure for the digital economy by verifying identities in real time and stopping fraud.