Senior AI Engineer

CrowdStrike

AI Engineer developing agentic AI solutions and CI/CD pipelines for CrowdStrike's AI technologies. Lead engineering delivery across platforms while ensuring production readiness and observability.

Posted 7/17/2026full-timeRemote • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining AI-driven systems, with a strong focus on scalable architecture, automation, and integration within enterprise environments. Proficient in leveraging modern AI frameworks and DevSecOps practices to enhance operational efficiency and decision-making.

Highest-signal resume keywords

Python ProficiencySalesforce DevelopmentAI Orchestration FrameworksCI/CD Pipeline ManagementDevSecOps Practices

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptJavaScriptSalesforce ApexLightning Web ComponentsLangChainDockerKubernetesVector DatabasesCI/CD Pipelines

Soft Skills

LeadershipCollaborationProblem-SolvingCommunication

Tools & Technologies

GitHub ActionsJenkinsTerraformAWS BedrockVertex AIAgentcoreSemantic KernelCrewAIAutoGenMCP

Industry Keywords

Agentic AIRAG SystemsEvent-Driven ArchitectureObservabilityAutomationSupply-Chain SecurityInfrastructure as CodeMulti-Tenant IsolationSemantic SearchDecision-Making Enhancement

Tech Stack

Tools & technologies

AWSCloudDockerJavaScriptJenkinsKubernetesPythonSOAPTerraformTypeScript

About the role

Key responsibilities & impact

Lead engineering delivery for agentic AI capabilities across GTM stakeholders and technology stacks (Salesforce, Slack, third-party apps, and in-house platforms), owning requirements through production deployment and post-release observability
Design and build LLM-powered workflows, autonomous agents, and multi-agent systems using Agentcore, Slack, Model Context Protocols (MCPs), LangChain, and LangGraph — then ship them via automated pipelines you maintain
Define scalable enterprise AI architecture patterns: model routing, orchestration, memory management, context-window governance, and multi-tenant isolation strategies
Design and optimize RAG systems, semantic search pipelines, vector retrieval strategies, and enterprise knowledge-grounding frameworks for GTM data domains
Build and maintain Salesforce Apex, Lightning Web Components, Platform Events, and Agentforce agent actions, integrating them with AI back-ends through secure, event-driven patterns
Build and operate platform observability stacks (tracing, logging, alerting) and AI-specific metrics while managing infrastructure-as-code (Terraform / CDK) across AWS Bedrock and Vertex AI
Implement DevSecOps and evaluation frameworks: supply-chain security, prompt benchmarking, hallucination reduction, and automated regression testing for non-deterministic outputs
Define error handling, fallback strategies, and graceful degradation patterns for non-deterministic AI systems, including circuit-breaker patterns at both the application and infrastructure layers
Retire legacy integrations and replace them with modern, agentic, event-driven architectures, eliminating manual toil through automation and self-healing runbooks
Champion engineering excellence: code reviews, runbook documentation, blameless post-mortems, and capacity planning that spans both application logic and underlying compute
Evaluate AI vendors and platforms with a strategic build-vs-buy mindset, factoring in total cost of ownership, compliance posture, and operational burden
Identify, scope, and automate manual GTM processes to increase organizational leverage and reduce time-to-insight for go-to-market teams

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, or a related field
5+ years of software engineering experience, with meaningful exposure to both application development and platform/infrastructure responsibilities
Strong proficiency in Python and TypeScript/JavaScript for AI application development, automation scripting, and infrastructure tooling
Hands-on production experience with agentic AI frameworks, document parsing and structured extraction pipelines, autonomous agents, and LLM-powered systems at enterprise scale
Solid working knowledge of modern AI orchestration frameworks: LangGraph, Semantic Kernel, CrewAI, AutoGen, MCP, and/or LangChain
Demonstrable experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, or Copado) and practicing GitOps or trunk-based delivery for both application and infrastructure code
Proficiency with container and orchestration runtimes (Docker, Kubernetes or equivalent) and familiarity with service mesh, secrets management, and configuration management patterns
Salesforce development experience: Apex, LWC, REST/SOAP integrations, Platform Events, and Agentforce agent actions
Proficiency with vector databases (Pinecone, pgvector, Weaviate, or similar) and retrieval optimization techniques for RAG systems
Solid understanding of DevSecOps practices: supply-chain security, SAST/DAST integration, secrets rotation, and least-privilege cloud IAM
Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.

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
Great Place to Work Certified™ across the globe