Director, Cloud Engineering

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Altos Labs is looking for a Director of Cloud Engineering who will lead the cloud infrastructure engineering and CI/CD teams to deliver services and solutions for our development teams. The team will interact with a broad range of internal teams focused on various aspects of life sciences, software development, AI/ML engineering, and data science and engineering. Leading the team will require a comprehensive understanding of the modern cloud native stack and the emerging technologies in scalable and distributed computing.

What You Will Contribute to Altos

• Lead and drive Data and ML Engineering team of ML Engineers and Data Engineers globally to design and build the data and analytics platform, the data/ML pipelines, and operationalize reproducible ML models, across all domains within the scope of Altos Labs Institutes. 
• Partner with Data Science and AI teams and the Lab stakeholders to translate the research into well engineered operationalized ML models. Proactively manage stakeholder expectations and outcomes by engaging in cross-functional collaboration.
• Lead the design of ML deployments with focus on optimizing ML models for performance, scalability and reliability with focus of continuous improvement.
• Lead Features Engineering activities to ensure there are automated data pipelines and adequate data integrity for building and ensuring continuous operations of ML models.
• Partner with scientific and lab operations leadership and key stakeholders to define Data and ML solutions requirements and deliver solutions that delight. Get alignment over the key design choices and the tradeoffs with the stakeholders.
• Build and Implement the best practices and foundations for Data and ML Engineering for all of Altos Labs. Push the envelope on the best practices as it applies to life science. 
• Collaborate with the open source community building tools and models in life science research and support the community to extend the state of the art. 
• Run internal technical checks and audits of all Engineering delivery on the Platform, and complying with external performance, privacy, security, and related audits.
• Provide guidance and architectural oversight to ensure that the Data and ML engineering solution is aligned to the overall Artificial Intelligence and Machine Learning (AI/ML) strategy and architecture.
• Create transparent governance and cost management across all data and ML projects.
• Hire, lead and develop talented data and ML engineers responsible for building complex scientific software deployed on cloud, on-prem, or desktop.
• Lead, inspire, coach, and mentor the team of developers and engineers while growing their technical skills and fostering job satisfaction. Develop and maintain a culture of innovation and operational efficiency in the team.
• Champion an inclusive and diverse global mindset to attract a diverse talent pool that includes effective coaching and development.
• Lead technical discussions with senior executives that drive decisions and implementations.

Key Responsibilities

• Deliver cloud platform services across a global organization over a hybrid multi-cloud infrastructure, including compute, storage, managed services, and high performance computing. 
• Be the subject matter expert and evangelist for cloud best practices and principles across the organization. 
• Drive the strategic planning and scaling of Altos’ cloud infrastructure to meet the current and future needs of the business. 
• Drive efficiency by leveraging automation and innovations at scale. The scientific compute and storage challenges of Altos will require out-of-the-box transformative thinking. Develop and maintain a culture of innovation and operational efficiency in the team.
• Hire, lead and develop talented software and DevOps engineers responsible for building and managing hybrid cloud systems.
• Build and maintain secure cloud implementations, automated provisioning of infrastructure and applications, and leverage CI/CD Pipelines for fast, reliable, and consistent deployments. Implement cybersecurity and audit controls for all cloud deployments. 
• Evaluating and recommending product and service selection, gaining approval, and developing implementation strategies for new technologies while meeting the organizational goals of security, reliability, and performance. 
• Work closely with leaders of the scientific cores, labs, software and ML engineering teams to deliver cloud capabilities that meet the scientific and business needs. 
• Work in partnership with IT and Operations to translate deployed solutions into operational activities and tasks. 
• Lead, inspire, coach, and mentor the team of developers and engineers while growing their technical skills.
• Foster cross-functional team collaboration to ensure engineered solutions meet availability, performance, resiliency, security, and operational efficiency criteria.
• Champion an inclusive and diverse global mindset to attract a diverse talent pool that includes effective coaching and development.
• Lead technical discussions with senior executives that drive decisions and implementations.
• Works with program management to provide estimates, timelines, project plans, and status reports to the rest of the organization for cloud infrastructure and solutions. 

Minimum Qualifications

• BA/BS (preferred MS) degree in Computer Science, Engineering, Mathematics or related technical field, or equivalent practical experience
• Excellent communications (verbal and written), able to collaborate and rally support. 
• Deep experience working with vendors and outsourcing organizations for workforce scaling. 
• Experience automating infrastructure provisioning and management, using systems like: Terraform, Ansible, Chef, Puppet, AWS CloudFormation, etc.
• Experience in managing large-scale infrastructure and automation.
• Familiarity with standard IT security practices such as identity and access management, data protection, encryption, certificate and key management
• Experience building services in a cloud environment (AWS, GCP, or Azure)
• Experience with Docker, Kubernetes, and container based environments that can handle scale from small to very large / enterprise
• Strong programming and scripting fundamentals (PHP, Python, Go, JavaScript, Shell)
• Experience designing, building, and deploying scalable cloud-based and hybrid system architectures
• DevOps CI/CD Tools such as CloudBees Jenkins, CloudBees CD, Ansible, GitLab, SonarQube, Twistlock, CheckMarx, Artifactory
• Experience with Integrated Solution Testing, Automated Performance and Regression/Functional Testing
• 10+ years of hands-on experience building PaaS and IaaS solutions, and technical operations.
• 7+ more years of people management experience leading infrastructure and development teams, including developing strong and motivated teams. 
• Experience with Linux / UNIX

Preferred Qualifications

• Track record on delivering infrastructure at scale, preferably in a global enterprise setting. 
• Flexibility, ability to think on your feet, and strong problem solving skills
• Demonstrated track record dealing well with ambiguity, prioritizing needs, and delivering measurable results
• Entrepreneurial innovation mindset. 
• Experience working successfully with distributed teams at remote locations
• Experience mentoring DevOps and software engineers
• Experience instilling a culture of innovation, ownership, collaboration, and results. 
• Strong problem solving skills – ability to assess a problem and determine an effective course of action with sustainable solution
• AWS / GCP / Azure or similar Cloud Certification
• Graduate degree in Computer Science, Engineering, Mathematics or related technical field, or equivalent practical experience.
• 10+ years of experience working directly with engineering teams.
• 5+ years of people management experience, managing engineers.
• Experience in managing remote/distributed teams across time zones. Managing outsourced resources.
• 3+ years of experience in driving strategy and scalable architecture for operationalizing Data and ML pipelines into production.
• Experience in partnering with product and program management teams.
• Strong knowledge and experience with cloud services (AWS/GCP/Azure), DevOps workflow, cloud-native platforms (containers, Kubernetes, serverless, etc.) and tools (such as Git), and infrastructure as code (IaC) tools (such as CloudFormation or Terraform).
• Experience in managing and troubleshooting distributed systems, such as Apache Hadoop, Apache Spark and Apache Kafka, and public cloud IaaS/PaaS.
• Experience in algorithms, data query and process automation, evaluation of datasets and complex data modeling. 
• Experience in Natural Language Processing (NLP), Machine Learning & Artificial Intelligence.
• Knowledge of open-source data science programming languages e.g., Python, Scala, R, Tensorflow, open-source libraries, e.g., Keras, and open-source distributed computing frameworks, e.g., Apache Spark, PySpark. Experience with Platforms like H2O, Sage maker, MLFlow, Anaconda etc.
• Experience managing the technical launch of data / ML products and subsequent releases, productionalizing, refreshing and scaling data models to additional data, within the domains of Life Sciences and Healthcare. 
• Expertise in leveraging standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation for Data and ML deployments.

Preferred Skills

• Flexibility, ability to think on your feet, and strong problem solving skills.
• Demonstrated track record dealing well with ambiguity, prioritizing needs, and delivering measurable results.
• Entrepreneurial innovation mindset. 
• Experience working successfully with partner teams at remote locations.
• Experience mentoring software engineers.
• Strong problem solving skills – ability to assess a problem and determine an effective course of action with sustainable solution.
• Familiarity with standard IT security practices such as identity and access management, data protection, encryption, certificate and key management.
• AWS or similar Cloud Certification.