Senior Manager, AI Engineering

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.