At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
Role Overview
We are seeking a Platform Lead to spearhead our ML Ops infrastructure, cost-optimisation, and deployment strategies. You will manage a talented team of DevOps engineers while remaining deeply technical and hands-on. Your primary mission is to build, scale, and secure the foundational platforms for our machine learning (ML) and generative AI (GenAI) models while maintaining financial accountability.
Your Impact
- Team Leadership & Collaboration: Lead and manage a dedicated DevOps team, mentoring both junior and senior engineers while collaborating closely with Data Science and Engineering leaders.
- Infrastructure Strategy & Automation: Define the infrastructure roadmap for AI/ML workloads and automate provisioning across cloud environments using Infrastructure as Code (IaC).
- MLOps & LLMOps Engineering: Architect, maintain, and optimise robust MLOps/LLMOps pipelines and CI/CD frameworks for continuous model deployment.
- GenAI Production Deployment: Deploy Large Language Models (LLMs) into production environments, ensuring high availability, low latency, and optimal performance for GenAI applications.
- FinOps & Budget Management: Establish FinOps frameworks to track, allocate, and forecast AI infrastructure spend, managing high-cost GPU/CPU cloud budgets.
- Resource Efficiency & Unit Economics: Implement auto-scaling, spot instances, and down-scaling policies to eliminate waste, while providing full visibility into the unit economics of training and serving LLM models.
- Observability & Incident Response: Establish 24/7 incident response, telemetry, and observability metrics to monitor system performance, model drift, and data pipelines.
- Data Governance & Security: Enforce strict data governance, platform security, and compliance protocols across all AI/ML infrastructure.
Your Skills
- Extensive production experience deploying and supporting ML systems.
- Proven track record of leading engineering teams.
- Demonstrated experience with Generative AI and LLM deployment patterns.
- A proven history of reducing cloud spend on large-scale AI clusters.
- Experience with tools like MLflow, Kubeflow, LangSmith, or Phoenix.
- Expertise in AWS/GCP/Azure cost tools, Kubecost, or Cloudability.
- Extensive background of Kubernetes (K8s), Docker, and service meshes.
- Expert knowledge of Terraform, Ansible, Jenkins, or GitHub Actions.
- Proficient in Python, Bash, or Go.
- Familiarity with Triton Inference Server, vLLM, or Hugging Face TGI.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to [email protected] before taking any further action in relation to the correspondence.
Candidate data processed during our recruitment activities is handled in accordance with our Candidate Privacy Notice. This may include the use of artificial intelligence or automated tools to assist our team in evaluating qualifications.
Skills Required
- Extensive production experience deploying and supporting machine learning systems
- Proven experience leading engineering teams
- Experience with generative AI and large language model deployment patterns
- Demonstrated history of reducing cloud spend on large-scale AI clusters
- Experience with MLflow, Kubeflow, LangSmith, or Phoenix
- Experience with AWS, GCP, or Azure cost-management tools, Kubecost, or Cloudability
- Extensive experience with Kubernetes, Docker, and service meshes
- Expert knowledge of Terraform, Ansible, Jenkins, or GitHub Actions
- Proficiency in Python, Bash, or Go
- Familiarity with Triton Inference Server, vLLM, or Hugging Face TGI
Anaplan Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anaplan and has not been reviewed or approved by Anaplan.
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Strong & Reliable Incentives — Earnings potential in sales is considered good or fair, with on‑target earnings achievable when plans are met. This indicates variable pay can meaningfully boost total compensation when targets are hit.
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Healthcare Strength — Medical, dental, and vision coverage are described as strong, complemented by mental‑health resources and EAP support. Company‑wide paid wellbeing days reinforce the health and wellness focus.
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Parental & Family Support — Equitable parental and caregiver leave are highlighted alongside fertility and adoption support. Family‑forming programs such as Carrot are part of the offering.
Anaplan Insights
What We Do
Anaplan is building a future where connected leaders and teams are able to constantly adapt, transform and reinvent their businesses. We make it possible to share actionable insights, empower and unleash creativity, and drive innovation. With Anaplan, finance and operational leaders across the organization can model complex scenarios, forecast continuously with added intelligence, and make agile decisions with confidence.
