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!
About the Role
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.
Mandatory Software Engineering Expertise
Candidates must have significant hands-on software development experience building large-scale production systems.
Languages
- Python (Expert)
- Java / Scala / Go
- SQL
Software Engineering
- 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
Cloud & Platform Engineering
- AWS / Azure / GCP
- Docker
- Kubernetes
- Kafka
- Spark / PySpark
- Airflow
- Databricks
- Delta Lake
- Iceberg
- Snowflake
- Redshift
- BigQuery
- Azure Synapse
DevOps / MLOps
- 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
Observability
- Prometheus
- Grafana
- OpenTelemetry
- ELK
- Splunk
Forecasting & Predictive AI Expertise
Classical Time Series
- 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
Machine Learning
- XGBoost
- LightGBM
- CatBoost
- Random Forest
- Extra Trees
- Elastic Net
- Bayesian Regression
- GLM
- GAM
- SVM
- KNN
Deep Learning Forecasting
- 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
Probabilistic Forecasting
- Quantile Forecasting
- Bayesian Forecasting
- Prediction Intervals
- Scenario Forecasting
- Ensemble Forecasting
- Hierarchical Forecasting
- Monte Carlo Simulation
Optimization
- 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
Enterprise Predictive AI Use Cases
Demand Planning
- Demand Forecasting
- Demand Sensing
- SKU Forecasting
- Product Forecasting
- Category Forecasting
- Store Forecasting
- Promotion Lift
- New Product Forecasting
- Cannibalization Analysis
- Lost Sales Prediction
Supply Chain
- 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
Finance
- Revenue Forecasting
- ARR Forecasting
- MRR Forecasting
- Financial Planning
- Expense Forecasting
- Cash Flow Forecasting
- Budget Forecasting
- Margin Forecasting
- Profitability Forecasting
- Driver-Based Planning
Sales
- Sales Forecasting
- Pipeline Forecasting
- Opportunity Scoring
- Win Probability
- Territory Planning
- Sales Capacity Planning
- Sales Performance Forecasting
Pricing
- Dynamic Pricing
- Price Elasticity
- Markdown Optimization
- Promotion Optimization
- Revenue Optimization
- Price Recommendation
- Assortment Optimization
Workforce
- Headcount Forecasting
- Workforce Planning
- Capacity Planning
- Attrition Prediction
- Resource Utilization
- Skills Demand Forecasting
Customer Analytics
- Churn Prediction
- Customer Lifetime Value
- Recommendation Systems
- Next Best Action
- Customer Segmentation
- Cross-sell/Upsell Models
- Propensity Modeling
Risk & Operations
- Fraud Detection
- Credit Risk
- Operational Risk
- Predictive Maintenance
- Failure Prediction
- Quality Prediction
- Root Cause Analysis
- SLA Prediction
Statistical & Mathematical Expertise
- Bayesian Statistics
- Frequentist Statistics
- Econometrics
- Probability Theory
- Hypothesis Testing
- Experimental Design
- Causal Inference
- Survival Analysis
- Time Series Analysis
- Multivariate Statistics
Feature Engineering
- Lag Features
- Rolling Statistics
- Window Functions
- Trend Extraction
- Seasonality Modeling
- Holiday Effects
- Weather Variables
- External Regressors
- Feature Selection
- Feature Drift Detection
Explainable AI
- SHAP
- LIME
- Partial Dependence Plots
- ICE
- Counterfactual Explanations
- Feature Attribution
AI Frameworks
- PyTorch
- TensorFlow
- JAX
- Scikit-learn
- Statsmodels
- Prophet
- Darts
- GluonTS
- NeuralForecast
- PyTorch Forecasting
- Ray
- Ray Tune
- Optuna
Preferred Qualifications
- 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.
Ideal Candidate
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 people@anaplan.com before taking any further action in relation to the correspondence.
