A remote Data & ML role at CrowdStrike.
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Original listing text, shown exactly as published by the company.
This role sits at the intersection of AI application engineering and platform reliability within CrowdStrike’s Core Tech, Go To Market IT Apps Team — a team of Architects, Engineers, QA, BSAs, and Product Owners delivering highly Reliable, Scalable, and Secure Infrastructure and Automation Services across GTM Applications to accelerate Business Velocity and Operational Excellence. As a hybrid AI Engineer (Dev + DevOps), you will build and own the full lifecycle of agentic AI solutions: from designing LLM-powered workflows and autonomous agents to engineering the CI/CD pipelines, infrastructure-as-code, platform observability, and DevSecOps practices that make those solutions production-grade and enterprise-ready. As part of the GTM AI Pod, every member is expected to embrace Agentic AI technologies, operate with an open-source AI engineering mindset, and actively contribute to building the next generation of intelligent GTM workflows. You will not hand off your code to another team to deploy — you own it end to end.
Shift Time: 2.00 pm - 11.00 pm IST
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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.
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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.
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Define scalable enterprise AI architecture patterns: model routing, orchestration, memory management, context-window governance, and multi-tenant isolation strategies.
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Design and optimize RAG systems, semantic search pipelines, vector retrieval strategies, and enterprise knowledge-grounding frameworks for GTM data domains.
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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.
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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.
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Implement DevSecOps and evaluation frameworks: supply-chain security, prompt benchmarking, hallucination reduction, and automated regression testing for non-deterministic outputs.
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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.
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Retire legacy integrations and replace them with modern, agentic, event-driven architectures, eliminating manual toil through automation and self-healing runbooks.
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Champion engineering excellence: code reviews, runbook documentation, blameless post-mortems, and capacity planning that spans both application logic and underlying compute.
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Evaluate AI vendors and platforms with a strategic build-vs-buy mindset, factoring in total cost of ownership, compliance posture, and operational burden.
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Identify, scope, and automate manual GTM processes to increase organizational leverage and reduce time-to-insight for go-to-market teams.
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Bachelor’s degree in Computer Science, Engineering, or a related field.
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5+ years of software engineering experience, with meaningful exposure to both application development and platform/infrastructure responsibilities.
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Strong proficiency in Python and TypeScript/JavaScript for AI application development, automation scripting, and infrastructure tooling.
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Hands-on production experience with agentic AI frameworks, document parsing and structured extraction pipelines, autonomous agents, and LLM-powered systems at enterprise scale.
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Solid working knowledge of modern AI orchestration frameworks: LangGraph, Semantic Kernel, CrewAI, AutoGen, MCP, and/or LangChain.
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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.
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Proficiency with container and orchestration runtimes (Docker, Kubernetes or equivalent) and familiarity with service mesh, secrets management, and configuration management patterns.
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Salesforce development experience: Apex, LWC, REST/SOAP integrations, Platform Events, and Agentforce agent actions.
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Proficiency with vector databases (Pinecone, pgvector, Weaviate, or similar) and retrieval optimization techniques for RAG systems.
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Solid understanding of DevSecOps practices: supply-chain security, SAST/DAST integration, secrets rotation, and least-privilege cloud IAM.
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Salesforce Platform Developer II, Application Architect, or DevOps Engineer certification.
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Experience building Slack apps, Slack Workflow Builder, or Slack-integrated agentic workflows.
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Hands-on experience with Salesforce Einstein / Agentforce platform development.
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Demonstrated contributions to open-source AI or DevOps tooling (LangChain, LlamaIndex, Terraform providers, or similar).
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Exposure to fine-tuning, RLHF, or model evaluation pipelines on domain-specific GTM datasets.
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Experience designing or operating model routing platforms, enterprise AI control planes, or multi-model gateway patterns (e.g., LiteLLM, OpenRouter).
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Background in platform engineering, SRE, or cloud infrastructure with a measured focus on SLOs, error budgets, and reliability engineering practices.
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Familiarity with AI governance, responsible AI frameworks, or MLOps maturity models as they apply to enterprise GTM systems.
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CrowdStrike
Data & ML
30 open roles on Sydicom
CrowdStrike Holdings, Inc. is an American cybersecurity technology company based in Austin, Texas. It provides endpoint security, threat intelligence, and cyberattack response services. The company was co-founded in 2011 by George Kurtz, Dmitri Alperovitch, and Gregg Marston. Kurtz serves as the CEO. CrowdStrike went public on the Nasdaq in 2019 and joined the S&P 500 index in 2024.
Source: Wikipedia
