Senior AI SDLC Engineer

CrowdStrike

. Design and build agentic workflows that automate software development lifecycle activities from code generation and review to testing and release .

Posted 9/24/2026full-timeRemote • Oregon • United StatesSenior💰 $140,000 - $215,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in backend engineering and AI technologies, with a focus on building and optimizing workflows for software development lifecycle activities. Proficient in LLM-agent infrastructure and observability tooling to enhance decision-making and streamline processes.

Highest-signal resume keywords

Backend Engineering ExperienceLLM-Agent InfrastructureGo and/or Python ProficiencyObservability Tooling DevelopmentBenchmark-Driven Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend EngineeringKubernetes SystemsLLM Application MechanicsAI Technologies UtilizationPrompt DesignEvent Pipeline OptimizationA/B TestingCost/Governance DashboardsGraph-Based Context SystemsSubagent Orchestration

Soft Skills

Comfort with AmbiguityCollaboration with Engineering Teams

Tools & Technologies

AI Coding Agent FrameworksObservability ToolingInternal Developer Platforms

Certifications & Qualifications

Background and Fingerprint Checks

Industry Keywords

Software Development LifecycleAutomated WorkflowsModel RoutingContext-Grounding SystemsDecision-Making Enhancement

Tech Stack

Tools & technologies

KubernetesPythonGo

About the role

Key responsibilities & impact

Design and build agentic workflows that automate software development lifecycle activities from code generation and review to testing and release
Improve context-grounding systems so agents resolve the right information on the first try
Tune model routing to match tasks with suitable models while considering cost efficiency
Build observability and quality tooling, including dashboards, usage insights, and benchmark suites
Establish internal benchmarks based on real-world tasks such as bug detection, review quality, and latency
Partner with engineering teams to identify workflow friction and create automated, agent-driven capabilities
Contribute to responsible and effective AI adoption across the organization

Requirements

What you’ll need

5+ years of backend/platform engineering experience, ideally with production Kubernetes systems
Hands-on experience building or operating LLM-agent infrastructure, including harnesses, tool-integration protocols, or subagent orchestration
Strong understanding of LLM application mechanics, including context windows, prompt design, caching, and reasoning/latency tradeoffs
Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes
Comfort working from ambiguous, evolving specs
Go and/or Python proficiency
Experience building internal developer platforms, observability tooling, or cost/governance dashboards
Experience with modern AI coding agent frameworks or SDKs
Familiarity with graph-based context systems, including knowledge graphs and entity resolution, feeding LLM applications
Background instrumenting or optimizing large-scale event pipelines
Prior experience running a benchmark-driven optimization program, including A/B testing and Pareto-frontier tracking, for a production system
Must periodically undergo and pass additional background and fingerprint checks consistent with government customer requirements

Benefits

Comp & perks

Market leader in compensation and equity awards
Comprehensive physical and mental wellness programs
Competitive vacation and holidays for recharge
Paid parental and adoption leaves
Professional development opportunities for all employees regardless of level or role
Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections
Vibrant office culture with world class amenities
Eligibility for bonuses
Equity grants
Health insurance
401k
Paid time off