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AI/ML Engineer – Systems Intelligence & Automation

CirrusLabs
  • Location not stated
  • 9 months ago
  • AI/ML
  • AI
  • Data Modeling
  • Python
  • Neo4j
  • Incident Management
  • ServiceNow
  • Jira
9 months ago
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We are CirrusLabs. Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments. We strive to maintain integrity with our employees and customers. Every action we take is driven by value. The core of who we are is through our well-knit teams and employees. You are the core of a values driven organization.

You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve.

You are excited about creating change because your skills can help the greater good of every customer, industry and community. We are hiring a talented< J ob Title >to join our team. If you're excited to be part of a winning team, CirrusLabs ( http://www.cirruslabs.io) is a great place to grow your career.

Role: AI/ML Engineer – Systems Intelligence & Automation
Location: Remote USA
Duration: Long Term

Role Overview
Hiring for a single AI/ML Engineer role responsible for building intelligent systems that reason over complex, structured data to drive deterministic decisions, root-cause diagnosis, asset and service intelligence, and workflow automation across large-scale environments. The engineer will design end-to-end AI solutions—from data modeling and ML/LLM development to APIs and integrations—that improve accuracy, observability, and automation across policy, cloud, service, and request workflows.

Key Responsibilities
  • Design and implement AI/ML and rule-based hybrid systems that evaluate structured inputs (e.g., IPs, ports, services, assets, policies) and return deterministic, explainable outcomes.
  • Build reasoning and flow-analysis engines that trace multi-step dependencies, identify failure points, and generate concise, human-readable diagnostic summaries.
  • Develop AI models and validation engines to detect conflicts, anomalies, overlaps, and misconfigurations in large-scale allocation, asset, and configuration datasets.
  • Model relationships between endpoints, services, dependencies, and cloud assets using graph- or relationship-based approaches, supporting service mapping and health intelligence.
  • Ingest and correlate telemetry, observability, and governance data to assess health, detect degradation patterns, and support audit, compliance, and MTTR reduction goals.
  • Build APIs and chat/assistant-style interfaces that expose these intelligence capabilities for real-time and on-demand workflows and ITSM/enterprise platforms.
  • Implement explainability and audit layers that surface rule paths, reasoning traces, and decision justifications for technical and non-technical stakeholders.
  • Continuously refine models and workflows using user feedback, monitoring signals, and performance metrics.

Must-Have Skills & Experience
  • 3–5+ years of hands-on AI/ML engineering experience with strong Python skills.
  • Proven experience building production-grade AI systems that combine rule-based logic with ML (e.g., validation engines, decision engines, or policy-as-code style systems).
  • Experience working with structured and semi-structured datasets (policies, telemetry, asset inventories, allocations, service maps, or similar).
Strong background in at least one of:
  • Graph traversal, relationship modeling, or knowledge/graph-based reasoning, or
  • Dependency analysis, causal inference, or multi-step flow/root cause analysis.
  • Experience developing and integrating APIs for model inference, including real-time or near-real-time analytics use cases.
  • Demonstrated experience with at least one of: anomaly detection, pattern recognition, classification, or clustering on operational/observability/governance-style datasets.
  • Practical experience with LLMs or conversational AI for guided workflows, prompt/response design, and structured output generation.
  • Strong data engineering and feature engineering skills to prepare, validate, and enrich large datasets for AI workloads.

Nice-to-Have Skills
  • Knowledge graphs or graph databases (e.g., Neo4j) used for service, asset, or policy reasoning.
  • Explainable AI (XAI) techniques and building auditable, traceable decision paths.
  • Familiarity with cloud governance, compliance, or risk datasets and concepts.
  • Experience integrating with ITSM, workflow, or incident management platforms (e.g., ServiceNow, Jira).
  • Prior work on reducing MTTR, escalation volume, or improving reliability through AI-driven diagnostics and automation.

AI/ML Engineer – Systems Intelligence & Automation · CirrusLabs

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