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!
We are building the next generation of AI-powered Enterprise Planning. We are looking for an exceptional Predictive AI & Forecasting Engineering leader who combines deep expertise in software engineering, forecasting, machine learning, optimization, and distributed systems.
This is not a traditional Data Scientist or GenAI role. We are seeking a software engineer first who has architected, built, deployed, and scaled production-grade Predictive AI platforms powering enterprise decision-making.
The ideal candidate has experience building intelligent planning systems for Finance, Supply Chain, Sales, Workforce, Operations, and Enterprise Planning, capable of serving millions of predictions with high availability, low latency, and enterprise-grade reliability.
What You'll Do- Architect and build enterprise-scale Predictive AI platforms from the ground up.
- Design highly scalable forecasting engines supporting millions of predictions.
- Develop distributed machine learning systems for batch and real-time inference.
- Build autonomous forecasting pipelines with continuous learning and automated retraining.
- Design reusable AI platforms, feature stores, model registries, and inference services.
- Build production-ready AI microservices with enterprise-grade reliability.
- Improve forecast accuracy using statistical, machine learning, and deep learning techniques.
- Design optimization engines supporting planning and decision intelligence.
- Partner with Product, Data, and Engineering to deliver next-generation AI capabilities.
- Drive architecture, code quality, engineering excellence, observability, and operational maturity.
Candidates must have significant hands-on software development experience building large-scale production systems.
Languages- Python (Expert)
- Java / Scala / Go
- SQL
- Object-Oriented Design
- SOLID Principles
- Design Patterns
- Clean Architecture
- Domain Driven Design
- Distributed Systems
- Microservices Architecture
- REST & gRPC APIs
- Event-Driven Architecture
- Multi-threading & Concurrency
- Asynchronous Programming
- High-throughput, Low-latency Systems
- Data Structures & Algorithms
- System Design
- Performance Engineering
- Secure Coding
- API Security
- AWS / Azure / GCP
- Docker
- Kubernetes
- Kafka
- Spark / PySpark
- Airflow
- Databricks
- Delta Lake
- Iceberg
- Snowflake
- Redshift
- BigQuery
- Azure Synapse
- CI/CD
- Infrastructure as Code
- MLflow
- Kubeflow
- SageMaker
- Vertex AI
- Azure ML
- Feature Store
- Model Registry
- Automated Retraining
- Model Monitoring
- Drift Detection
- Experiment Tracking
- A/B Testing
- Canary Deployment
- Rollback Strategies
- Prometheus
- Grafana
- OpenTelemetry
- ELK
- Splunk
- ARIMA
- SARIMA
- SARIMAX
- VAR
- Prophet
- Holt-Winters
- ETS
- TBATS
- Croston
- Theta
- STL
- MSTL
- State Space Models
- Dynamic Linear Models
- Bayesian Structural Time Series
- Gaussian Processes
- Kalman Filters
- Hidden Markov Models
- XGBoost
- LightGBM
- CatBoost
- Random Forest
- Extra Trees
- Elastic Net
- Bayesian Regression
- GLM
- GAM
- SVM
- KNN
- LSTM
- GRU
- Seq2Seq
- Temporal Convolution Networks
- N-BEATS
- N-HiTS
- DeepAR
- DeepState
- Temporal Fusion Transformer
- Informer
- Autoformer
- FEDformer
- PatchTST
- TimesNet
- TiDE
- Chronos
- Moirai
- TimeGPT
- Transformer-based Forecasting
- Diffusion Models for Time Series
- Quantile Forecasting
- Bayesian Forecasting
- Prediction Intervals
- Scenario Forecasting
- Ensemble Forecasting
- Hierarchical Forecasting
- Monte Carlo Simulation
- Linear Programming
- Mixed Integer Programming
- Non-linear Optimization
- Dynamic Programming
- Bayesian Optimization
- Reinforcement Learning
- Stochastic Optimization
- Constraint Programming
- Genetic Algorithms
- Particle Swarm Optimization
- Simulated Annealing
- Demand Forecasting
- Demand Sensing
- SKU Forecasting
- Product Forecasting
- Category Forecasting
- Store Forecasting
- Promotion Lift
- New Product Forecasting
- Cannibalization Analysis
- Lost Sales Prediction
- Inventory Optimization
- Multi-Echelon Inventory
- Replenishment Planning
- Supply Planning
- Procurement Planning
- Production Planning
- Capacity Planning
- Logistics Forecasting
- Warehouse Optimization
- Supplier Risk Prediction
- Lead Time Prediction
- Revenue Forecasting
- ARR Forecasting
- MRR Forecasting
- Financial Planning
- Expense Forecasting
- Cash Flow Forecasting
- Budget Forecasting
- Margin Forecasting
- Profitability Forecasting
- Driver-Based Planning
- Sales Forecasting
- Pipeline Forecasting
- Opportunity Scoring
- Win Probability
- Territory Planning
- Sales Capacity Planning
- Sales Performance Forecasting
- Dynamic Pricing
- Price Elasticity
- Markdown Optimization
- Promotion Optimization
- Revenue Optimization
- Price Recommendation
- Assortment Optimization
- Headcount Forecasting
- Workforce Planning
- Capacity Planning
- Attrition Prediction
- Resource Utilization
- Skills Demand Forecasting
- Churn Prediction
- Customer Lifetime Value
- Recommendation Systems
- Next Best Action
- Customer Segmentation
- Cross-sell/Upsell Models
- Propensity Modeling
- Fraud Detection
- Credit Risk
- Operational Risk
- Predictive Maintenance
- Failure Prediction
- Quality Prediction
- Root Cause Analysis
- SLA Prediction
- Bayesian Statistics
- Frequentist Statistics
- Econometrics
- Probability Theory
- Hypothesis Testing
- Experimental Design
- Causal Inference
- Survival Analysis
- Time Series Analysis
- Multivariate Statistics
- Lag Features
- Rolling Statistics
- Window Functions
- Trend Extraction
- Seasonality Modeling
- Holiday Effects
- Weather Variables
- External Regressors
- Feature Selection
- Feature Drift Detection
- SHAP
- LIME
- Partial Dependence Plots
- ICE
- Counterfactual Explanations
- Feature Attribution
- PyTorch
- TensorFlow
- JAX
- Scikit-learn
- Statsmodels
- Prophet
- Darts
- GluonTS
- NeuralForecast
- PyTorch Forecasting
- Ray
- Ray Tune
- Optuna
- Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, Operations Research, Econometrics, or a related quantitative discipline.
- 10+ years of software engineering experience with at least 5+ years building production-grade Predictive AI and Forecasting platforms.
- Proven track record designing scalable AI systems, distributed data platforms, and enterprise SaaS products.
- Strong background in system design, distributed computing, cloud-native architecture, and MLOps.
- Experience delivering enterprise AI solutions across Finance, Supply Chain, Sales, Workforce, or Integrated Business Planning (IBP) domains.
- Excellent communication and technical leadership skills, with the ability to mentor engineers and influence architecture across teams.
A software engineering leader who is equally comfortable discussing distributed systems, microservices, system design, MLOps, and cloud architecture as they are implementing state-of-the-art forecasting models, optimization algorithms, and predictive AI solutions. This role is best suited for engineers who have built enterprise-scale Predictive AI platforms, rather than research-focused data scientists or GenAI application developers.
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
- Proven experience leading AI/ML teams in a SaaS or enterprise software environment.
- Deep expertise in time series forecasting and machine learning.
- Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Proven track record of delivering complex technical projects on time with high quality.
- Excellent communication, collaboration, and stakeholder management skills.
- Track record of delivering impactful AI solutions in a fast-paced, agile environment.
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.
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