AI Architect

Job Description

AI/ML Architecture Design:

Design and architect the time series ML lifecycle, including ingestion, feature engineering, model training, evaluation, and serving.

Define architecture for univariate, multivariate, and predictive models (ARIMA, Prophet, LSTM, XGBoost, etc.).

Evaluate and integrate anomaly segmentation techniques.

Able to create complete end to end RAG pipeline.

MLOps & Lifecycle Management

Establish best practices for CI/CD pipelines, MLflow-based model tracking, versioning, and rollback.

Align model deployment across batch (Databricks jobs) and real-time (AKS / Azure ML Endpoints) inference.

Collaborate with platform teams to operationalize retraining, drift detection, and alerting.

Data Architecture & Feature Stores

Design feature pipelines using Delta Lake and offline/online feature stores (e.g., Feast, Delta + Redis).

Work with data engineering to align with Bronze → Silver → Gold zone processing across Azure Data Lake.

Stakeholder Collaboration

Partner with product owners, energy engineers, and visualization teams to translate insights into actionable dashboards and external APIs.

Lead data scientists and ML engineers to design, prototype, and productionize energy optimization models

Teck Stack

Azure Databricks, Azure ML, Azure Kubernetes Service, Delta Tables , Azure Data Lake Gen2, Azure Blob Storage, Time series, Predictive Modelling, RAG/LLM based Gen AI.

Mandatory Skills: AI for Product Software Engineering.

Desired Skills and Experience

AI ARCHITECT, ML, SOFTWARE ENGINEERING