We are looking to hire AI Tech Lead who owns the architectural backbone of our AI ecosystem.

What You Will Do

- Architectural Leadership Define and evolve the end to end architecture for RAG pipelines, agent frameworks, and distributed inference systems. Prioritize scalability, latency, and UX aligned output determinism.

- Rigorous Evaluation Build custom evaluation harnesses for AI agents, RAG, and LLM reasoning. Move beyond out of the box metrics with domain specific scoring, adversarial tests, and regression suites.

- Advanced AI Paradigms Continuously integrate cutting edge methodologies (structured reasoning, tool use optimization, memory systems, multi agent collaboration).

- Technical Mentorship Coach developers on AI security, token economics, UX patterns, and safe deployment practices. Establish coding standards and architectural guardrails.

Required Qualifications

- Proven leadership delivering production grade ML/AI systems.

- Strong foundations in vector math, LLM internals, embeddings, agent frameworks, and evaluation science.

- Knowledge of Google s GECX is a robust bonus.

- Expertise in systems level programming, distributed architecture, and performance critical code.

Skillset Requirements





- Systems Architecture Expertise designing distributed AI systems, multi agent frameworks, and scalable RAG pipelines.

- LLM Internals Deep understanding of transformer mechanics, attention patterns, tokenization, and inference optimization.

- Evaluation Science Ability to design adversarial tests, regression suites, and domain specific scoring functions.

- AI Security Knowledge of jailbreak prevention, prompt injection defense, secure tool use, and zero trust agent routing.

- Tokenomics Ability to optimize token usage, context windows, and cost latency trade-offs.

- Distributed Systems Experience with load balancing, sharding, concurrency, and high availability inference clusters.

- Observability Familiarity with tracing, logging, telemetry, and agent level debugging.

- DevOps for AI CI/CD for model updates, containerization, GPU orchestration, and rollout strategies.

- Mentorship & Leadership Ability to enforce engineering discipline, code quality, and architectural guardrails.

- Responsible AI & Governance Guardrail design, content-safety policy, and audit/traceability for regulated deployments.

📌 AI Tech Lead (Brampton)
🏢 Ju0026M Group
📍 Brampton