Head of Applied AI & Data Engineering

Job Title: Head of Applied AI & Data Engineering

Location: Toronto, Hybrid

Department: Technology/Engineering

Type: Full-time

About Us

We’re on a mission to build a safer Canada by Empowering Frictionless Trust in Every Interaction.

Fraud and scams are rising threats to people’s financial security, privacy, and trust. We help businesses and organizations fight fraud, prevent scams, and provide secure and frictionless access to products and services – protecting Canadians when it matters most.

We believe that earning trust is the foundation of every great customer relationship. And we’re building the technology, expertise, and partnerships to make that possible at scale.

About the Role

EnStream is reimagining the future of trusted digital access – leveraging intelligent systems to enable seamless, secure, and adaptive experiences.

We’re seeking a hands-on, full-stack technical leader who will shape the strategy, architecture, and implementation of EnStream’s AI and data platforms.

As Head of Applied AI & Data Engineering, you’ll combine technical expertise, strategic vision, and a builder’s mindset. You’ll be deeply hands-on – designing and developing core systems in the early stages – and scaling a high-performing cross-functional team over time. This role spans Data Science, Machine Learning Engineering, and Data Platform Engineering, driving innovation that enhances user trust while balancing experience, security, and compliance.

Your ability to align diverse stakeholders, foster a culture of innovation and accountability, and deliver real-world systems with measurable impact will be key to your success.

What You’ll Do

Build the Intelligent Trust Engine

• Design and develop models for identity confidence, behavioral analytics, and dynamic risk scoring.
• Define and drive the vision for EnStream’s applied AI and data platforms, balancing innovation with operational excellence.
• Design and deliver production-ready AI/ML systems – from data ingestion and model training to real-time decisioning and monitoring.
• Architect scalable, secure, and privacy-aware infrastructure to support EnStream’s trusted access services.
• Develop and maintain foundational data platforms, streaming pipelines, feature stores, and MLOps tooling.

Hands-On Engineering

• Roll up your sleeves to write production-grade code, build APIs, and deploy pipelines in Python, SQL, and relevant frameworks.
• Stand up initial systems for model scoring, telemetry, and observability to accelerate early delivery.
• Make key technical decisions, balancing velocity with long-term sustainability and performance.

Cross-Functional Leadership

• Build and scale a multidisciplinary team of ML engineers, data scientists, and data platform specialists.
• Partner with Product, Telecom, and enterprise teams to align AI capabilities with EnStream’s strategic goals.
• Foster a collaborative, high-integrity culture that values trust, transparency, and continuous learning.

Customer-Centric Innovation

• Collaborate with stakeholders to identify high-impact use cases that enhance seamless access and user trust.
• Stay ahead of emerging AI technologies (LLMs, embeddings, vector search) and thoughtfully integrate them where valuable.
• Ensure systems are explainable, resilient, and compliant with privacy and security standards.

What You Bring

• 10+ years of experience across software, data, and AI/ML – with deep coding ability and technical design expertise.
• Hands-on experience building AI systems in production, ideally in high-integrity domains like trust, identity, or financial access.
• Fluency in modern ML frameworks (PyTorch, TensorFlow), MLOps stacks (MLflow, Airflow, Docker), and cloud-native platforms (AWS, GCP).
• Strong engineering skills in Python, SQL, and data processing – comfortable building full pipelines and APIs.
• Experience with real-time systems (Kafka, Spark/Flink), microservices, and streaming architectures.
• Working knowledge of LLMs, vector embeddings, or semantic similarity tools – and how to integrate them responsibly.
• Ability to lead through doing – shifting between technical execution, architectural design, and team leadership.

Bonus Points

• Experience in building systems for identity verification, authentication, or trusted access.
• Knowledge of graph-based models, behavioral biometrics, or anomaly detection.
• Familiarity with privacy-preserving ML techniques, federated learning, or security-conscious ML deployment.
• Background in telecom, public infrastructure, fintech, or regulated sectors.

Why Join Us?

• Build from first principles – lead both strategy and implementation of Canada’s digital trust infrastructure.
• Work hands-on with real-world problems where your code directly impacts people’s access to essential services.
• Join a culture that values thoughtful innovation, ethical engineering, and long-term trust-building.
• Grow into a transformative leadership role – shaping the architecture, team, and systems that define digital trust in Canada.

Ready to Help Build a Safer Canada?

If you’re a principled builder, systems thinker, and mission-driven leader – we’d love to talk.