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Lead AI Solutions Engineer
2 months ago
Lineaje Inc is a leader in delivering comprehensive security management solutions tailored for software supply chains. Our cutting-edge technology provides an extensive overview of software components, highlighting dependencies and authenticating the entire chain to avert security breaches. By safeguarding the integrity and security of software supply chains, we enable organizations to function securely and effectively in a digital landscape. Join us in our endeavor to elevate software security and propel technological progress in the sector.
Position Overview
We are in search of a forward-thinking and technically skilled AI Lead to spearhead the creation and implementation of sophisticated artificial intelligence solutions within our company. This crucial position entails directing AI projects, designing advanced AI frameworks, and ensuring seamless integration with our current systems. The perfect candidate will have extensive knowledge in AI technologies, particularly in Python, cybersecurity, supply chain risk management, and software supply chain security.
Core Responsibilities
- AI Strategy Development:
- Formulate and execute a progressive AI strategy that aligns with the organization’s business objectives and technological roadmap.
- Assess and utilize the latest advancements in AI to maintain a competitive advantage.
- Architectural Design:
- Create robust and scalable AI architectures designed to fulfill specific business requirements, emphasizing cloud-native architecture and design patterns.
- Ensure AI solutions operate efficiently in a Federal environment and are FedRAMP authorized, optimizing both costs and resources.
- Risk Management in Supply Chains:
- Deploy AI solutions to identify, evaluate, and mitigate risks within the software supply chain.
- Devise strategies to bolster software supply chain security, ensuring the integrity and resilience of our systems.
- Enhancing Threat Intelligence:
- Leverage AI technologies to improve threat intelligence capabilities, identifying and addressing cybersecurity threats and vulnerabilities.
- Integrate AI-driven threat intelligence with existing security frameworks to enhance threat detection and response times.
- Collaboration with Cybersecurity Teams:
- Partner closely with cybersecurity teams to ensure AI solutions are in harmony with and enhance existing security systems and protocols.
- Facilitate the integration of AI technologies into cybersecurity strategies, strengthening the overall security posture.
- Project Management:
- Oversee the complete AI project lifecycle, ensuring strict compliance with timelines and quality standards.
- Data Management:
- Collaborate with data teams to guarantee high-quality data collection, preprocessing, and analysis for AI initiatives.
- Establish and enforce data governance policies, ensuring adherence to privacy regulations and standards.
- AI Development:
- Lead the development of innovative machine learning models utilizing Python and related technologies.
- Implement strategies for AI explainability and transparency to foster trust in AI solutions.
- Ethics in AI:
- Incorporate AI ethics and fairness principles into the design and deployment of AI systems.
- Ensure AI solutions are developed with a focus on human-centered design principles.
- Technology Utilization:
- Employ containerization technologies such as Docker and Kubernetes for effective AI application deployment and management.
- Apply DevOps practices and tools to guarantee smooth AI system integration and continuous delivery.
- Utilize collaboration tools like Slack, Jira, and Asana for efficient teamwork and project management.
- Use version control systems like Git to manage AI codebases and track modifications.
- Innovation and Research:
- Encourage a culture of innovation by exploring new AI methodologies and applications relevant to our industry.
- Conduct research and pilot projects to assess the feasibility and advantages of emerging AI technologies.
- Team Leadership:
- Guide and mentor a team of AI engineers and data scientists, fostering an environment of growth and collaboration.
- Identify and address skill gaps through targeted training and development initiatives.
- Commitment to Learning:
- Dedicate oneself to ongoing learning and professional development to remain abreast of rapidly evolving AI technologies and trends.
Qualifications
- Education:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline. A PhD is advantageous.
- Experience:
- 8+ years of experience in AI/ML development, with a proven track record of leading successful AI projects.
- Extensive experience in designing and implementing AI architectures.
- Domain expertise in cybersecurity, supply chain risk management, and software supply chain security.
- Technical Skills:
- Proficiency in Python is essential, with a strong history of utilizing Python for AI/ML development.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Experience with cloud-native architectures and technologies, including AWS, MongoDB, Open Search, EKS, and Fargate.
- Knowledge of containerization technologies like Docker and Kubernetes.
- Familiarity with DevOps practices and tools for continuous integration and delivery.
- Leadership Skills:
- Demonstrated ability to lead and inspire high-performing technical teams.
- Strong project management capabilities, with a focus on delivering results in a dynamic environment.
- Communication Skills:
- Exceptional written and verbal communication skills, with the ability to convey complex technical concepts to diverse audiences.