Practice Lead DevOps

Candidate Profile: Practice Lead - DevSecOps, DataOps, AI-MLOps

Summary:

Highly accomplished and forward-thinking Practice Lead with 12+ years of experience architecting and managing DevSecOps, DataOps, and AI-MLOps strategies. Expertise in transforming complex digital environments within the manufacturing sector, driving innovation, security, and operational efficiency. Adept at building and mentoring high-performing teams, aligning technology initiatives with business objectives, and fostering a culture of continuous improvement and data-driven decision-making.

Job Description:

As the Practice Lead for DevSecOps, DataOps, and AI-MLOps, you will spearhead the development and implementation of cutting-edge practices to optimize software delivery, data management, and AI/ML model operationalization across our digital enterprise. Key responsibilities include:

Strategic Leadership:

Define and execute the strategic vision for DevSecOps, DataOps, and AI-MLOps practices, aligning them with business goals and industry best practices.

Team Management:

Lead, mentor, and grow a team of engineers, architects, and specialists. Foster a collaborative and innovative environment.

Practice Development:

Establish and refine processes, standards, and tools for secure software development, data governance, and AI/ML model deployment.

Security Integration:

Champion a security-first culture by embedding security practices throughout the software development lifecycle.

Data Governance:

Ensure data quality, integrity, and compliance with regulatory requirements.

Automation & Optimization:

Drive automation initiatives to streamline processes, reduce costs, and improve efficiency.

Stakeholder Collaboration:

Collaborate with cross-functional teams, including IT, engineering, data science, and business stakeholders, to ensure alignment and effective communication.

Innovation & Research:

Stay abreast of emerging technologies and trends, and evaluate their potential to enhance our DevSecOps, DataOps, and AI-MLOps capabilities.

Skills and Expertise:

Technical Proficiencies:

DevSecOps:

CI/CD pipelines, Infrastructure as Code (Terraform, Ansible), containerization (Docker, Kubernetes), security scanning tools (SAST, DAST), cloud platforms (AWS, Azure, GCP)

DataOps:

Data integration and ETL tools (e.g., Apache Spark, Kafka), data warehousing solutions, data quality and governance frameworks

AI-MLOps:

Machine learning platforms (e.g., TensorFlow, PyTorch, scikit-learn), model deployment frameworks (e.g., MLflow, Kubeflow), model monitoring and management

Methodologies:

Agile, Scrum, Kanban

ITIL

Security and Compliance:

Security frameworks (e.g., NIST, ISO 27001)

Data privacy regulations (e.g., GDPR, CCPA)

Compliance standards relevant to manufacturing (e.g., FDA)

Soft Skills:

Exceptional leadership and communication skills

Strategic thinking and problem-solving

Change management and stakeholder management

Mentoring and coaching

Experience:

12+ years of experience in IT, with a focus on DevOps, Security, Data Management, or AI/ML Operations.

5+ years of experience in a leadership role managing DevSecOps, DataOps, or AI-MLOps teams.

Demonstrated success in implementing and scaling DevSecOps, DataOps, or AI-MLOps practices in a complex enterprise environment.

Experience working in the manufacturing industry is highly preferred.

Proven ability to drive cultural change and foster a collaborative, data-driven environment.

Education:

Bachelor's degree in Computer Science, Engineering, or a related field.

Master's degree is preferred.

Relevant certifications (e.g., AWS Certified DevOps Engineer, Certified Information Systems Security Professional (CISSP), Certified Data Management Professional (CDMP)).