Forward Deployed AI Engineer

EQ Bank | Equitable Bank•Toronto, ON

17d

About The Position

We are looking for a Forward Deployed AI Engineer who can bridge the gap between business strategy and real-world AI delivery. This role is about more than building models—it’s about taking AI from idea to production, integrating it into core systems, and ensuring it delivers measurable business value. You will combine hands-on engineering expertise with practical AI implementation, helping teams adopt AI in a way that is scalable, secure and usable.

Requirements

Strong experience building scalable, distributed systems.
Deep knowledge of APIs, microservices, and service-based architectures.
Deep knowledge of Cloud-native development (Azure preferred).
Deep knowledge of CI/CD, containerization, and deployment automation.
Experience with event-driven systems, data pipelines and data platforms.
Hands-on experience building LLM-powered applications in production.
Strong Experience with prompt design and evaluation.
Strong Experience with model limitations (hallucination, variability, context constraints).
Strong Experience with agent design and orchestration workflows.
Strong Experience with tool/API integrations.
Strong Experience with RAG and knowledge grounding patterns.
Experience across the full lifecycle: use case definition, solution design, integration, deployment, monitoring and optimization.
Strong understanding of AI observability (quality, latency, cost), reliability and system performance.
Experience working in regulated environments.
Strong awareness of data privacy and security.
Strong awareness of AI governance and controls.
Strong awareness of misuse prevention (incl. prompt injection risks).
Strong awareness of auditability and human-in-the-loop safeguards.

Responsibilities

Play a lead technical role in designing and delivering AI-enabled solutions across the enterprise.
Design, build, test, and deploy AI-enabled applications, services, and workflows.
Work with LLMs, intelligent agents, and automation frameworks to solve real business problems.
Take solutions from prototype to production, ensuring they are reliable and scalable.
Lead architecture and design for LLM integrations, Retrieval-Augmented Generation (RAG), Agent workflows and orchestration, and API and enterprise system integrations.
Ensure solutions are secure, reusable, and aligned with enterprise standards.
Define and apply reusable patterns and best practices for AI delivery.
Improve how teams build, deploy, and scale AI solutions.
Contribute to responsible and governed AI adoption.
Ensure solutions are production-ready (testing, monitoring, observability).
Troubleshoot issues, perform root cause analysis, and continuously improve systems.
Optimize for performance, cost, reliability, and user experience.
Work closely with product, architecture, platform, security, and business stakeholders.
Translate business needs into clear technical solutions and delivery plans.
Influence decisions through technical expertise, not authority.