Job Summary Technology Delivery Lead (TDL) – Toronto, Ontario

Hours: 37.5 per week

Pay: $96,900 - $136,800 CAD (plus discretionary variable compensation) Responsibilities - Serve as Solution Architect/Tech Lead for the delivery squad, final authority on design decisions.

- Define and own end‑to‑end system architecture: API contracts, service layers, data models, integration patterns between Go backend, React frontend, and PostgreSQL.
- Lead architecture reviews before code is written.
- Produce architectural artifacts such as sequence diagrams, component diagrams, ADRs, and API specs.
- Evaluate trade‑offs between velocity, maintainability, security, and cost.
- Define & enforce coding standards, branching strategies, and CI/CD pipeline quality gates.
- Champion AI‑native culture, integrating large language models into production and tooling.
- Lead GCP engineering: GKE clusters, BigQuery pipelines, Cloud Run, Pub/Sub, and related services.
- Architect data storage, ETL/ELT frameworks via Databricks, PySpark, BigQuery.
- Manage observability and monitoring with Google Cloud Operations Suite.
- Maintain infrastructure as code with Terraform.
- Collaborate on security & compliance, validate auth/authorization, and AI/ML responsible use.
- Participate in SAFe ceremonies: PI Planning, System Demos, Inspect & Adapt.
- Mentor engineers through pairing, code review, and design critique.
- Prioritize work and unblock teammates to meet sprint timelines.

Qualifications - Undergraduate degree in Computer Science, Software Engineering, or equivalent.

- 7+ years software engineering experience with at least 3 years in a tech lead or architect role.
- Experience designing and shipping production systems on Google Cloud Platform.




- Hands‑on experience integrating LLM/generative AI APIs into production applications.
- Backend engineering in Go and frontend in React + TypeScript.
- Experience with SQL, PostgreSQL, data modeling, ETL/ELT design.
- Proficiency with GCP services: GKE, GCS, BigQuery, Cloud Run, IAM, Secret Manager, Terraform.
- Knowledge of AI/ML LLM integration patterns, RAG, prompt engineering, embedding models.
- Experience with API design, system architecture, ADRs.
- Awareness of OWASP Top 10, authentication/authorization patterns.
- Understanding of Agile/SAFe practices and cross‑team dependency management.

Strong

Assets - Databricks and PySpark at enterprise scale.

- Experience in regulated financial services (data governance, audit trails).
- AI developer tooling (AI‑assisted coding platforms).
- Vertex AI model deployment and MLOps pipelines.
- Google Cloud Operations Suite for SLO definition, alerting, and distributed tracing.
- Human‑centered design practices in a design‑led delivery squad.
- Familiarity with OpenShift/Kubernetes on‑prem or hybrid. AI Mindset - Approach problems with an “AI first” thinking, asking what if AI could solve the issue.
- Shipped at least one AI‑powered feature into production and learned lessons.
- Critically evaluate AI claims and manage hallucinations, latency, and cost trade‑offs.
- Propose concrete AI‑powered features with clear sprint plans.

Benefits - Competitive base salary and variable compensation.

- Health and wellness advantages, retirement plans, paid time off.
- Learning and development opportunities with online platform and mentoring.
- Career growth within TD, path to Senior Technical Lead and Distinguished Engineer.

📌 Technology Delivery Lead (Toronto)
🏢 TD Bank
📍 Toronto