Senior Principal AI/ML Engineer

At Anaplan, we are looking for a strong Senior Principal AI/ML Engineer to join our team in Ottawa, Canada, as a member of a global engineering organization across the US, UK, Israel, and India.

Are you a creative problem solver who can both give and receive feedback? Do you lead with inclusion, collaboration, and openness? Do you have strong experience with high-scale B2B and B2C platforms?

As a Senior Principal Platform Engineer, you'll be crafting and helping build the next generation AI/ML driven Anaplan Platform. You have proven and relevant experience in Artificial Intelligence and Machine Learning, using LLM, prompt engineering, and RAG to deliver bots and augmented AI virtual assistant software products to build state-of-the-art software platforms of the future. You're comfortable with full-stack systems design for the hybrid cloud and hands-on distributed systems programming with extensive knowledge of Java, JVM, Python, Rust, Linux internals, and container orchestration.

This role is an immediate full-time position. If you're ready to roll up your sleeves and seek unique problems that no one is solving in the tech space yet, keep reading.

This role will require you to be in our Ottawa office two days a week. 

Your Impact:

• Play a key technical leadership role in designing and implementing the next generation AI/ML enabled Anaplan Platform
• Design and implement new interactive AI capabilities on highly scalable distributed systems and shared services infrastructure in a hybrid cloud environment using Java11, Kotlin, Rust, Kubernetes, and Docker.
• Collaborate with global teams to build and deliver machine learning solutions into the Anaplan platform
• Develop and deploy machine learning models focused on Generative AI and Large Language Models
• Design and build retrieval-augmented generation systems to improve search and recommendation functionalities
• Use data-driven approaches to measure the quality of our platform and be a strong enthusiast for security and observability.
• Implement code to the desired specification following the standard methodologies, including tests (TDD) and documentation.
• Serving as a senior team member and ensuring architecture and design is at its best.
• Mentor engineering team members.
• Contribute intellectual property through patent generation.
• Apply your judgment to determine what to defer and what problem needs to be solved now, taking a pragmatic, business-oriented approach to evolving solutions over time.
• Influence infrastructure architecture by sharing your expertise.

Your Qualifications:

• BS degree in Computer Science, related technical field, or equivalent practical experience as a professional Platform Engineer.
• 12+ years of professional experience as a Software Engineer, working on AI and ML infused Backend and Platform Engineering, data science, predictive and forecasting analytics
• Proven and extensive experience with AI, Machine Learning, Deep Learning, Linear Regression, Conversational AI, bots, Natural Language Processing, LLM, prompt engineering, RAG
• Proven experience in building and maintaining a SaaS product at scale
• Experience with cloud storage S3, NFS, NetApp OnTap, Cohesity
• Containers and container-orchestration tools like Docker and Kubernetes.
• Distributed Systems and programming techniques.
• Monitoring and metrics infrastructure (Grafana, Loki, Prometheus, Splunk, SignalFx).
• Public Cloud (e.g., AWS / GCP/ Azure).
• Experience with the design, implementation, and deployment of scalable API services based on a micro-services architecture
• Knowledge or experience with messaging systems such as Kafka, AMQP (RabbitMQ), ZeroMQ
• Experience working with containers and container-orchestration tools like Docker and Kubernetes
• Experience with Public Cloud (e.g., AWS / GCP/ Azure) Database management systems (SQL, noSQL)

Technologies you'll work with:

• Programming languages: Java11, Kotlin, Rust, Python
• Persistence: MySQL, CRDB, Redis, S3, NFS, NetApp OnTAP
• Experience with Big Data, Spark, Kafka, Jupyter Notebooks
• Container and Orchestration: Kubernetes/Docker, Helm
• Event Driven Architecture: Kafka, RabbitMQ
• Public cloud: AWS, GCP, Azure
• CI/CD/Build/Deploy: GitHub, Gradle, Maven, Jenkins, Harness, Artifactory
• Telemetry: Grafana, Loki, Prometheus

#LP-SP1

•

Last updated on Aug 22, 2024