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AI and Data Team Manager
Bugcrowd. Define and drive the technical roadmap for AI, ML, and data systems, overseeing development, deployment, and operationalization to ensure robust performance, scalability, and direct alignment with key business strategy and requirements.
Posted 4/20/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $137,600 - $212,850 per yearWebsite
Tech Stack
Tools & technologiesAmazon RedshiftAWSCyber SecurityPython
About the role
Key responsibilities & impact- Define and drive the technical roadmap for AI, ML, and data systems, overseeing development, deployment, and operationalization to ensure robust performance, scalability, and direct alignment with key business strategy and requirements.
- Lead, mentor, and grow a small high-performing team of data scientists and ML engineers, cultivating a culture of technical excellence, accountability, and continuous learning.
- Direct the entire lifecycle—from design to deployment—of robust data pipelines, scalable model training, and innovative AI/ML applications.
- Guide the development, tuning, deployment, and MLOps of Machine Learning models for cybersecurity.
- Architect, govern, and optimize large-scale, high-performance data pipelines essential for securely and efficiently processing massive vulnerability, asset, and activity datasets.
- Collaborate closely with infrastructure teams to architect AI workloads and data pipelines that meet stringent requirements for security, efficiency, and scalability, particularly within multi-tenant and regulated environments.
- Serve as the primary technical subject matter expert and liaison.
Requirements
What you’ll need- 5+ years of experience in Data Science, ML Engineering, or Data Engineering, with 2+ years in a technical leadership or team lead role.
- Strong architectural understanding of LLM technologies, RAG architectures, prompt engineering, ML Ops, and secure API integration with AI systems.
- Master’s degree or higher in Computer Science, Information Systems, or a related quantitative field.
- Deep expertise with Python, AWS services (S3, Lambda, Batch, Glue, Bedrock, Step Functions, Redshift), and ML frameworks.
- Proven experience successfully leading a team to build and deploy end-to-end ML pipelines—from data ingestion to model deployment, monitoring, and MLOps.
- Ability to design, manage, and govern secure data architectures for large-scale, multi-tenant, and high-security environments.
- Excellent communication skills with a demonstrated ability to mentor engineers, influence technical direction, and present complex concepts to both technical and non-technical audiences.
Benefits
Comp & perks- Bonuses
- Discretionary bonus program or commission plan
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Data ScienceMachine Learning EngineeringData EngineeringMLOpsPythonLLM technologiesRAG architecturesprompt engineeringsecure API integrationend-to-end ML pipelines
Soft Skills
leadershipmentoringcommunicationinfluencingtechnical directionaccountabilitycontinuous learningcollaborationproblem-solvingpresentation
Certifications
Master’s degree in Computer ScienceMaster’s degree in Information SystemsMaster’s degree in a related quantitative field