Engineer III, AI SDLC Engineer

CrowdStrike

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

Posted 10/5/2026full-timeRemote • United StatesMid-LevelSenior💰 $120,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in backend and platform engineering with a focus on building and optimizing LLM-agent infrastructure, observability tooling, and automated workflows. Proficient in Go and Python, with a strong understanding of AI technologies and their application in enhancing decision-making and operational efficiency.

Highest-signal resume keywords

Backend Engineering ExperienceLLM-Agent InfrastructureGo And/Python ProficiencyObservability Tooling DevelopmentAI Technologies Utilization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend EngineeringKubernetes SystemsLLM Application MechanicsAI Coding Agent FrameworksEvent Pipeline OptimizationBenchmark-Driven OptimizationPrompt DesignCost Efficiency AnalysisAutomated Workflow CreationSubagent Orchestration

Soft Skills

Comfort With AmbiguityCollaborative Problem Solving

Tools & Technologies

Observability ToolingCost/Governance DashboardsGraph-Based Context SystemsKnowledge GraphsEntity Resolution

Industry Keywords

Software Development LifecycleAI AdoptionWorkflow Friction IdentificationModel RoutingUsage Insights

Tech Stack

Tools & technologies

KubernetesPythonGo

About the role

Key responsibilities & impact

Design and build agentic workflows that automate software development lifecycle activities, including code generation, review, 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 for 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 engineering 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 — harnesses, tool-integration protocols, subagent orchestration, or similar
Strong understanding of LLM application mechanics: 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 (knowledge graphs, entity resolution) feeding LLM applications
Background instrumenting or optimizing large-scale event pipelines
Prior experience running a benchmark-driven optimization program (A/B testing, Pareto-frontier tracking) for a production system

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
Bonuses
Equity grants
Health insurance
401k
Paid time off