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.  

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Senior Manager, AI Engineering