Senior Software Engineer - Agentic AI Foundations
New
CanadaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonJavaGoRESTful APIsDistributed Systems
Requirements
- 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.
- Background in multi-agent systems, workflow orchestration, or similar distributed coordination frameworks (Preferred).
- Exposure to building or using agent platforms (e.g., orchestration frameworks, tool registries, memory systems) or advanced prompt/LLM routing, caching, or fine-tuning pipelines (Preferred).
- Experience with evaluation frameworks, experimentation platforms, or ML systems (e.g., offline/online evals, A/B testing, or benchmarking agents and models) (Preferred).
- Experience specifically with AI safety, security, or policy systems (guardrails, policy engines, content filters, or responsible AI frameworks) (Preferred).
- Experience with retrieval systems, knowledge graphs, or data platforms used to ground LLMs and agents in enterprise context (Preferred).
- Experience in a founding, early-stage, or platform-building role where you defined patterns and paved paths for other teams (Preferred).
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).
- Uphold and model Socure’s leadership expectations for senior engineers: operating with strong product and systems thinking, influencing without authority, collaborating across functions, and raising the technical bar for the team.
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