Job
Description
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)).
