AI and Data Team Manager
New
B
BugcrowdCybersecurity
Remote - USFull-TimeManager
Salary137600 - 212850 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonCI/CDAWS LambdaPrompt EngineeringMLOps
Requirements
- 5+ years of experience in Data Science, ML Engineering, or Data Engineering
- 2+ years in a technical leadership or team lead role
- Strong architectural understanding of LLM technologies
- Strong architectural understanding of RAG architectures
- Strong architectural understanding of prompt engineering
- Strong architectural understanding of ML Ops
- Strong architectural understanding of 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
- Deep expertise with AWS services (S3, Lambda, Batch, Glue, Bedrock, Step Functions, Redshift)
- Deep expertise with ML frameworks
- Proven experience successfully leading a team to build and deploy end-to-end ML pipelines
- Ability to design, manage, and govern secure data architectures for large-scale, multi-tenant, and high-security environments
- Excellent communication skills to mentor engineers, influence technical direction, and present complex concepts
Responsibilities
- Define and drive the technical roadmap for AI, ML, and data systems, overseeing development, deployment, and operationalization.
- Lead, mentor, and grow a small high-performing team of data scientists and ML engineers.
- Direct the entire lifecycle of robust data pipelines, scalable model training, and innovative AI/ML applications to boost analyst and hacker productivity.
- Guide the development, tuning, deployment, and MLOps of Machine Learning models for cybersecurity.
- Ensure secure and compliant integration of cutting-edge generative AI models (via platforms like AWS Bedrock, OpenAI, Anthropic) with internal APIs and sensitive security datasets.
- Architect, govern, and optimize large-scale, high-performance data pipelines for processing vulnerability, asset, and activity datasets.
- Collaborate closely with infrastructure teams to architect AI workloads and data pipelines meeting security, efficiency, and scalability requirements.
- Serve as the primary technical subject matter expert and liaison, partnering with security research, product, and platform teams.
- Establish and manage best-in-class MLOps practices, including CI/CD pipelines, evaluation frameworks, and monitoring/observability tools.
- Oversee the design of robust, high-availability APIs and interfaces for seamless interaction between LLM agents and internal systems.
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