JD-2025-AIML-1: Senior AI/ML Engineer – Agentic AI

6 days ago

Toronto, Ontario, Canada Amyantek Full time $100,000 - $150,000 per year

JD-2025-AIML-1: Senior AI/ML Engineer – Agentic AI

Location: Toronto, ON (Hybrid)

Client: Applab/Loblaws

Type: Full-time Team: Machine Learning Platform / Digital & Data

About the Role

Loblaws Digital is hiring a Senior AI/ML Engineer with a strong emphasis on Agentic AI systems. This role focuses on building production-grade multi-agent workflows, LLM-powered automation, and scalable ML infrastructure on GCP. You will work on next-generation AI capabilities including Agentic AI, LangGraph-based pipelines, RAG architectures, and enterprise ML platforms supporting real-world retail and supply chain use cases. This is a high-priority hire and we are moving fast.

MUST-HAVE Requirements (Non-Negotiable)

Candidates must have all the following:

  • Agentic AI & LLM Development
  • Hands-on experience building Agentic AI systems using:
  • LangGraph (mandatory)
  • LangChain / LangSmith / LangServe
  • Multi-agent orchestration & tool calling
  • Proven experience deploying LLM applications in production (not just POCs).
  • Expertise in RAG pipelines, vector DBs (FAISS, Pinecone, Chroma, pgvector), memory models.
  • Strong skills in Prompt Engineering, LLM evaluation (RAGAS/TruLens), context optimization.
  • Engineering & Cloud
  • Advanced Python development for AI systems (FastAPI, async workflows, microservices).
  • Hands-on production experience with GCP:
  • Vertex AI
  • BigQuery
  • BigTable
  • Cloud Storage
  • Cloud Composer (Airflow)
  • Deep understanding of ML Ops / LLMOps:
  • CI/CD (GitHub Actions, Cloud Build, Jenkins)
  • Model deployment best practices
  • Docker, Kubernetes
  • Experience building end-to-end ML pipelines: ingestion → feature engineering → training → deployment

Experience Level

  • 5+ years of ML/AI engineering
  • 2+ years specifically with LLMs / Agentic AI
  • Experience working in enterprise or production-scale environments

What You'll Do:

Agentic AI & LLM Engineering (Primary Focus)

  • Build multi-agent AI workflows using LangGraph and advanced orchestration patterns.
  • Implement RAG pipelines, long-term memory, and LLM-driven automation for enterprise workflows.
  • Fine-tune, evaluate, and optimize LLMs for low latency and high reliability in production

ML Platform & Infrastructure

  • Architect and maintain scalable ML/LLM infrastructure on GCP.
  • Integrate ML workflows via Cloud Composer (Airflow) and standardized pipelines.
  • Develop LLMOps foundations including model monitoring, drift detection, evaluation frameworks.

Cloud, Data & Platform Engineering

  • · Optimize cloud compute/storage for performance and cost.
  • · Build automated, self-service tooling for Data Scientists and ML Engineers.
  • Implement observability: tracing, logging, monitoring, and failover strategies.

Soft Skills & Team Fit

  • Strong communicator; able to partner effectively with DS, DE, and product teams.
  • Curious, experimental thinker who explores new AI patterns.
  • Independent owner capable of leading complex initiatives from ideation to production.
  • Customer-first mindset to reduce friction for ML practitioners.

Qualifications

  • Bachelor's or Master's degree in CS, Engineering, AI/ML (mandatory due to vendor requirement).
  • Strong foundation in ML fundamentals, distributed systems, and cloud-native engineering.
  • Experience deploying scalable AI/ML solutions in production environments.

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