Senior AI Systems Engineer
Quick Summary
Lead the technical strategy and hands-on execution for building production-grade multi-agent systems and security chatbots. Scale Our Capabilities: Act as an accelerator for the team,
What We Offer
~2 min readSwimlane is redefining security operations with Agentic AI automation that empowers organizations to work smarter, respond faster, and stay ahead of threats. Our low-code platform combines automation, orchestration, and intelligent reasoning to unlock true operational autonomy across the modern SOC.
At Swimlane, we put people first. We foster a culture of innovation, trust, and continuous improvement—where your ideas matter and your work drives meaningful change. Join us and help build the next era of Agentic AI-powered security operations.
Senior AI Systems Engineer
Agentic AI & AI SOC
About the Role
~1 min readOur current team is firing on all cylinders to deliver core features, but as our product scope rapidly expands, we need a technical driver to help us scale. We are looking for a Principal AI Systems. Engineer to act as a pathfinder and shape the next generation of AI SOC capabilities in the Swimlane Turbine platform.
This position sits within Data Science but is fundamentally a software engineering and integration role—not a model-training role. You will take the wheel on applied LLM projects, driving the transition from single-prompt features to robust multi-agent systems and intelligent customer-facing security chatbots.
Responsibilities
~1 min read- →Drive Architectural Change: Lead the technical strategy and hands-on execution for building production-grade multi-agent systems and security chatbots.
- →Scale Our Capabilities: Act as an accelerator for the team, taking ownership of new AI feature development so we can keep pace with rapidly growing product demands.
- →Build Applied LLM Workflows: Design secure, maintainable workflows using for AI SOC use cases like alert triage, summarization, and workflow automation.
- →Own Evaluation (Evals): Create test sets, define success metrics (accuracy, faithfulness, latency), and run regression tests before and after changes for your features.
- →Monitor Production Behavior: Debug hallucinations and systematically reduce failure modes through better retrieval, prompting, and guardrails (not just "tweak the temperature").
- →Establish Engineering Standards: Define robust patterns for context engineering, tool design, retrieval, and harness engineering to ensure our agents are rigorously evaluated for quality and safety.●
- →Champion Security-First AI: Ensure data privacy, access controls, and prompt injection defenses are embedded deeply into our multi-agent architectures.
- →Collaborate Cross-Functionally: Work seamlessly across Data Science, Engineering, Product, and Platform teams to guide emerging AI capabilities from prototype to production.
Location & Eligibility
Listing Details
- First seen
- September 26, 2026
- Last seen
- September 27, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 57%
- Scored at
- September 27, 2026
Signal breakdown
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