Lead Architect AI & Agentic Systems in Halifax

Your responsibilities:

• Define and refine the long-term vision, strategy, and target architecture for AI-enabled operational services.

• Conduct discovery, assessment, and analysis of existing capabilities and operational processes.

• Identify opportunities for automation, self-service, and service optimisation.

• Develop strategic roadmaps and implementation plans aligned to business outcomes.

• Provide architecture leadership and technical guidance throughout the transformation journey.

• Collaborate with stakeholders to prioritise initiatives and define delivery approaches.

• Ensure solutions meet governance, security, compliance, and operational requirements.

• Support the transition from strategy and design into implementation and adoption.

• System Architecture & Strategy: Define the target architecture for agentic workflows, multi-agent orchestration, and Model Context Protocol (MCP) integrations across enterprise systems.

• Platform Scalability & Cloud Native Design: Architect decoupled, stateless microservices tailored for Kubernetes containerization, ensuring high availability, fault tolerance, and zero-downtime deployments.

• RAG & Memory Management Architecture: Oversee the architectural blueprint for Retrieval-Augmented Generation (RAG), vector knowledge stores (Cortex), and hybrid session memory (short-term & long-term persistence).

• Governance, Security & Responsible AI: Design security controls, data lineage, and privacy frameworks (including long-term data deletion and compliance guardrails) in strict alignment with Responsible AI standards.

• Cross-Functional Leadership: Guide senior engineers and technical leads through architectural decision records (ADRs), technical governance gates, and solution reviews.

• Kubernetes Platform Governance: Define and enforce architectural standards for Kubernetes-based deployments, including pod design principles, namespace isolation, resource quotas, autoscaling strategies (HPA/VPA), and rolling deployment patterns ensuring TESSA's agentic services operate as fully stateless, resilient, and production-grade workloads across cluster environments.

Your Profile

Essential skills/knowledge/experience:

• 8+ years of experience in enterprise software architecture, with at least 3+ years leading AI/ML or LLM-integrated platform architectures.

• Deep understanding of agentic orchestration protocols, Model Context Protocol (MCP), tool-use patterns, and multi-agent coordination.

• Proven track record with LangChain, LlamaIndex, vector databases, chunking strategies, embeddings, and context-window optimization.

• Strong expertise with Kubernetes, Docker, microservice decoupling, event-driven architecture, and REST/gRPC API design.

• Hands-on experience defining and enforcing Kubernetes architectural standards including pod design, namespace isolation, resource quotas, HPA/VPA autoscaling, and rolling deployment strategies to ensure fully stateless, production-grade workloads.

• Hands-on experience designing robust IAM, VPC-SC, rate limiting, and audit logging for AI/ML workloads.

• Proven experience in AI, AIOps, intelligent automation, and enterprise architecture.

• Strong understanding of conversational AI, large language models (LLMs), agent-based solutions, and automation platforms.

• Experience defining target-state architectures, strategic roadmaps, and digital transformation initiatives.

• Knowledge of IT Service Management (ITSM), operational processes, incident management, and service delivery models.

• Strong stakeholder engagement and consulting skills with the ability to translate business objectives into technology strategies.

• Experience leading cross-functional teams and influencing senior business and technology stakeholders.

• Familiarity with cloud-native architectures, APIs, integration patterns, governance, security, and compliance frameworks.

• Excellent analytical, problem-solving, communication, and presentation skills.