Senior Staff Software Engineer - AI/ML - Veza

Job Description

We are seeking a Senior Staff Software Engineer to serve as the technical visionary and architect for our multi-agent harness platform, and writing agents for our products. This is a high-leverage, tier-one leadership opportunity operating at the absolute frontier of Agent research and large-scale backend systems engineering.

In this role, you won't just implement agents—you will define the architectural patterns, scalability guardrails, and strategic direction for how intelligent, autonomous agents reason, decide, and secure the modern enterprise.

Qualifications

• Education: Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related technical field.
• Experience: 10+ years of professional software engineering experience, with a proven track record of technical leadership at a Staff or Senior Staff level. 2+ years of hands-on experience in architectural design and production deployment of GenAI technologies, multi-agent systems, LLM orchestration frameworks (e.g., LangChain, AutoGen), or Model Context Protocols (MCP).
• Technical Mastery: Expert-level proficiency in Python and Golang (or Java), with deep expertise in distributed systems, microservices architectures, and high-throughput API design. Deep understanding of Cloud Platforms (AWS, Azure, GCP) with experience designing or integrating with enterprise Identity and Access Management (IAM) environments and security fabrics.
• Execution & Ownership: A strong sense of product ownership. You have a history of taking ambiguous, 0-to-1 AI initiatives and scaling them to 1-to-100 enterprise realities.
• Communication: Exceptional communication skills with a demonstrated ability to distill complex AI reasoning and architectural trade-offs into clear, strategic narratives for both engineering teams and executive boardrooms.

What You Will Do

• Arcitect & Vision: Define the technical roadmap and architecture for Access AI Platform, ensuring high availability, low latency, and deterministic reliability.
• System Design: Lead the design of advanced agent orchestration layers, multi-agent communication, and sophisticated context/memory management.
• Productionize at Scale: Transition cutting-edge LLM capabilities and MCP frameworks from experimental prototypes into hardened, enterprise-grade pipelines within our identity access infrastructure.
• Technical Leadership: Act as a force multiplier across the engineering organization. Define engineering excellence, establish robust test/evaluation frameworks for non-deterministic AI systems, and mentor senior and staff-level engineers.
• Cross-Functional Influence: Partner closely with Product, Security, and Executive leadership to align technical investments with long-term business strategy, pioneering new capabilities from ideation to global deployment.