The Role
We are looking for a hands-on, highly experienced Senior Technical AI & ML Architect to lead the design, development, and implementation of scalable AI, ML, and GenAI solutions across our modern data platform.
This role requires deep technical expertise in Databricks, Azure cloud services, machine learning engineering, and enterprise data architecture.
You will work closely with product, engineering, and business stakeholders to deliver robust, future-proof AI/ML solutions that drive measurable business outcomes.
Your responsibilities:
Lead end-to-end architecture for AI/ML and GenAI solutions on Azure + Databricks.
Design scalable feature engineering, model training, deployment, and monitoring pipelines using Delta Lake, MLflow, and Feature Store.
Drive MLOps best practices, including CI/CD, model lifecycle management, and production observability.
Provide technical direction to engineering teams, ensuring high-quality, secure, and cost- efficient solution design.
Collaborate with product and business stakeholders to translate complex business needs into scalable technical architectures.
Ensure alignment with enterprise governance, platform standards, and Lakehouse principles.
Run technical reviews, mentor engineers, and champion modern engineering and AI delivery practices.
Essential skills/knowledge/experience:
Strong hands-on experience with Databricks (PySpark, Delta Lake, DLT, MLflow, Feature Store).
Solid understanding of Azure cloud services relevant to data and ML (ADLS, ADF, Functions, EventHub, Key Vault).
Proven experience delivering AI/ML and GenAI solutions (LLMs, embeddings, RAG, NLP, forecasting, optimisation models).
Strong Python and ML engineering knowledge (Scikit-Learn, TensorFlow/PyTorch).
Demonstrated experience with MLOps: CI/CD, model registry, monitoring, and retraining workflows.
Ability to create clear architecture artefacts (HLD/LLD, decision logs, patterns) and present them to technical and business leaders.
Strong stakeholder engagement skills with the ability to influence architecture decisions and guide teams.
Desirable skills/knowledge/experience:
Airline domain exposure (Booking, commercial, operations, loyalty etc).
Experience with Azure OpenAI, Prompt Flow, Cognitive Services.
Experience with vector databases.
Knowledge of ethical AI, model governance, and ML security.
Experience with data observability tools.
Databricks Certified Machine Learning Professional