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!
You will join the Predictive Intelligence engineering team within Anaplan, the group responsible for the Syrup platform and the family of forecasting and predictive services that power Anaplan’s verticalized solutions. The team builds and operates the ML platform, forecasting engines, and data processing services that deliver demand forecasting, inventory recommendations, and predictive insights to enterprise customers in retail, supply chain, and beyond. This role reports to the Director of Engineering for Predictive Intelligence and serves as the senior technical leader across the predictive intelligence pillar.
Your Impact
- Own the overall architecture and technical strategy for Anaplan’s predictive intelligence services across multiple verticalised solutions.
- Drive a unified architectural approach across disparate intelligence services, reducing duplication and establishing shared platform primitives for forecasting, model serving, and data processing.
- Provide hands-on design and implementation leadership for major features and platform initiatives, including writing and reviewing critical-path code where the work demands it.
- Define and oversee the MLOps strategy spanning model training, deployment, monitoring, and lifecycle management on Kubernetes across AWS, GCP, and Azure.
- Establish and evangelize engineering best practices across services, including standards for scalability, fault tolerance, observability, and operational excellence.
- Mentor senior engineers and partner closely with data scientists to elevate technical quality and shorten the path from research to production.
- Partner with Product, Data Science, and Platform leadership to shape the multi-quarter technical roadmap and influence cross-organisation decisions on predictive intelligence.
- Represent the AI engineering organisation in technical conversations and architectural reviews with outside teams.
Your Qualifications
- Strong experience working within Software Engineering, Principal or Architect-level role owning systems at scale.
- Deep expertise in Python and in designing and operating high-availability, production ML services.
- Hands-on experience designing and operating data and analytics platforms built on technologies such as Snowflake, Iceberg, Trino, and Postgres.
- Strong production experience with Kubernetes and at least one major cloud provider (AWS, GCP, or Azure), with working familiarity across multi-cloud environments.
- Demonstrated experience with MLOps tooling and patterns, including model registries, experiment tracking, and CI/CD for.
- Proven ability to lead architectural strategy across multiple teams and services, balancing long-term vision with pragmatic delivery.
- Strong communicator who can translate complex technical decisions into clear narratives for engineers, data scientists, product partners, and executives.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Preferred Skills
- Experience operating forecasting models in production, including gradient-boosted methods, neural networks, and constraint-based optimization solvers.
- Domain background in retail, supply chain, demand planning, or financial planning.
- Experience leading post-acquisition platform integration or cross-organisation architectural alignment across previously independent products.
- Open-source contributions to ML infrastructure, data processing, or related ecosystems.
- Advanced degree in Computer Science, Machine Learning, Statistics, or a related field.
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
- 12+ years professional software engineering experience, including 4+ years in a Principal or Architect-level role
- Deep expertise in Python and designing/operating high-availability production ML services
- Hands-on experience with data and analytics platforms such as Snowflake, Iceberg, Trino, and Postgres
- Strong production experience with Kubernetes and at least one major cloud provider (AWS, GCP, or Azure); familiarity with multi-cloud
- Demonstrated experience with MLOps tooling and patterns, including model registries, experiment tracking, and CI/CD
- Proven ability to lead architectural strategy across multiple teams and services
- Strong communication skills to explain complex technical decisions to engineers, data scientists, product partners, and executives
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
- Experience operating forecasting models in production (gradient-boosted methods, neural networks, constraint-based optimization)
- Domain background in retail, supply chain, demand planning, or financial planning
- Experience leading post-acquisition platform integration or cross-organization architectural alignment
- Open-source contributions to ML infrastructure, data processing, or related ecosystems
- Advanced degree in Computer Science, Machine Learning, Statistics, or a related field
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.
