AI/ML Engineer

Role snapshot

• Title: Senior AI Engineer

• Location: Toronto, ON (hybrid, 2–3 days on-site)

• Engagement: Full-time, leading AI delivery on Augmented enterprise client projects

• Level: Senior (6+ years of experience, 2+ years building production AI systems)

• Reports to: Head of AI Engineering

About the role

Augmented is hiring a Senior AI Engineer to lead the design and delivery of enterprise-grade AI systems for large clients in regulated industries. You will set technical direction, architect LLM and agent-based solutions, and make sure they are reliable, secure and cost-effective in production.

You will be the senior technical voice with client stakeholders and a mentor to the engineers around you.

Key responsibilities

• Architect end-to-end AI solutions: RAG platforms, multi-agent systems, AI assistants and workflow automation

• Make build-vs-buy and model selection decisions, balancing quality, latency, cost and data residency

• Define evaluation strategy, quality gates and red-teaming for LLM systems before and after release

• Set engineering standards for prompts, agents, tool use, observability and LLMOps across projects

• Design for security, privacy and compliance: PII protection, access controls, audit trails and responsible-AI policies

• Lead production rollouts, scaling, performance tuning and cost optimisation

• Translate business goals into AI roadmaps and present options and trade-offs to client technical and executive leaders

• Lead and mentor a team of AI engineers through design reviews, pairing and code reviews

• Contribute to pre-sales solutioning, estimates and proposals with Augmented leadership

Required qualifications

• 6+ years of software or ML engineering experience, including 2+ years delivering production LLM or GenAI systems

• Expert Python and strong software architecture skills (APIs, distributed systems, event-driven design)

• Deep experience with RAG, agents and tool use using frameworks such as LangGraph, LlamaIndex or custom orchestration

• Proven record designing LLM evaluation, monitoring and guardrails at scale

• Strong cloud architecture skills on Azure, AWS or GCP, including Kubernetes, IaC and CI/CD

• Experience leading technical teams and working directly with senior client stakeholders

• Legally entitled to work in Canada

Nice to have

• Fine-tuning, distillation or self-hosting of open-source models (vLLM, Hugging Face)

• Model Context Protocol (MCP) and enterprise agent integrations

• Classical ML and MLOps (MLflow, feature stores, model serving)

• Data platform experience with Databricks or Snowflake

• Experience in Life Sciences (GxP, clinical, commercial) or Financial Services (risk, fraud, compliance)

• Published work, open-source contributions or conference talks in AI

• Consulting or client-facing delivery background

Tech stack

• Languages: Python, SQL, TypeScript

• AI: LLM APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock), open-source models

• Orchestration: LangGraph, LlamaIndex, MCP, custom agent frameworks

• Retrieval: vector databases, hybrid search, re-rankers, knowledge graphs

• Serving & LLMOps: vLLM, MLflow, LangSmith / Langfuse, eval harnesses

• Cloud & DevOps: Azure or AWS, Kubernetes, Terraform, CI/CD

• Data: Databricks, Snowflake

Why Augmented

Augmented is an AI-native engineering delivery hub serving large enterprises in Life Sciences and Fintech, with teams in Toronto and the US.

• Shape AI strategy and architecture for major enterprise clients

• Small, senior teams with direct access to client decision-makers

• Lead AI-native delivery practices and modern tooling

How to apply

Apply through this posting with your resume and a short note on an AI system you architected and led to production (scale, design choices, results).

• Augmented is an equal opportunity employer. Accommodations are available on request at any stage of the hiring process.