Position : AI Technical Lead : Only Canada

Location : Brampton ON (Onsite)

Type of Job : Contract : 12 Months

Experience : 15+ Years

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 solid 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 Technical Lead : Only Canada - Brampton ON (Onsite)
🏢 KAnand
📍 Brampton