Posted 27 days ago
AI Tech Lead
@ J&M Group
Brampton, Ontario
SIGNALS
Overview
J&M Group is hiring an AI Tech Lead on a contract basis to own the architecture of its AI ecosystem. The work covers RAG pipelines, agent frameworks and distributed inference, plus evaluation harnesses and mentoring developers on AI security and deployment. The posting requires proven leadership delivering production ML/AI systems.
Responsibilities:
- Define end-to-end architecture for RAG pipelines and agent frameworks
- Build custom evaluation harnesses for agents and LLM reasoning
- Integrate emerging methodologies such as tool use and multi-agent collaboration
- Coach developers on AI security, token economics and safe deployment
Requirements summary:
- Proven leadership delivering production-grade ML/AI systems
- Strong foundations in vector math, LLM internals and embeddings
- Expertise in systems-level programming and distributed architecture
- Knowledge of Google GECX is a strong bonus
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-10-15
- First seen by our source
- 2026-11-11
- Source record updated
- 2026-11-11
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Lead |
| Department | Software development |
| Work setting | Office, Home |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
J&M Group
| Field | Value |
|---|---|
| Open jobs on Jobsy | 66 |
Job description
We are looking to hire AI Tech Lead who owns the architectural backbone of our AI ecosystem.
What You Will Do
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.
- 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 strong bonus.
- Expertise in systems level programming, distributed architecture, and performance critical code.
- 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.
Journal
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