AI Engineeer

TekStaff's Client has a current vacancy for a AI Engineeer

Job Description

AI Engineer Description

This is a fantastic opportunity for an experienced Senior AI Engineer to join the Loblaw Technology team.

The ideal candidate will be passionate about building reliable and practical AI agents and AI workflows powered by Large Language Models (LLMs). You

will use Python, LangGraph, Langfuse, Model Context Protocol (MCP), and Google Cloud to develop AI agents, Retrieval-Augmented Generation (RAG)

solutions, and production-ready AI services.

You will work in a fast-paced organization using Agile/Scrum methodologies and collaborate with product managers, software engineers, and business

stakeholders to deliver AI solutions for customer service and operational requirements.

Principal Responsibilities

Design and develop LLM-powered applications using Python

Build AI agents and workflows using LangGraph

Develop RAG solutions using enterprise data, embeddings, and vector search

Build and integrate MCP servers to connect AI agents with enterprise tools, data, and services

Implement LLM tracing, monitoring, and evaluation using Langfuse

Develop and deploy AI services on Google Cloud

Create APIs and integrations for AI capabilities

Write unit and integration tests to ensure solution quality

Evaluate AI outputs for accuracy, relevance, reliability, and safety

Monitor and troubleshoot AI applications in production

Collaborate with product, engineering, architecture, and business teams

Contribute to AI engineering standards and reusable development patterns

Mentor developers and provide guidance through design and code reviews

Remain current with developments in LLMs and generative AI

Required Skills and Experience

5+ years of professional software development experience

2+ years of experience developing agentic AI or LLM-powered applications

Strong Python development experience

Hands-on experience building applications with LLMs

Experience with LangGraph, LangChain, or a similar AI application framework

Experience with Langfuse or another LLM observability platform

Understanding of Model Context Protocol (MCP) and its use in connecting AI agents with tools and enterprise systems

Experience with Google Cloud services such as Vertex AI and BigQuery

Experience building RAG solutions using embeddings and vector search

Experience developing RESTful APIs using FastAPI, Flask, or a similar framework

Understanding of prompt engineering, tool calling, structured outputs, and context management

Experience with automated testing, Git, and CI/CD practices

Understanding of data privacy, AI safety, and responsible AI principles

Experience working with Agile methodologies

Excellent verbal and written communication skills

Desirable Skills and Experience

Hands-on experience developing or integrating MCP servers and clients

Experience with Gemini, OpenAI, Anthropic, or open-source LLMs

Experience with vector databases such as Vertex AI Vector Search, Pinecone, pgvector, or Supabase

Experience with Docker and containerized deployments

Familiarity with event-driven systems such as Pub/Sub

Familiarity with LLM evaluation frameworks

Experience working with high-traffic enterprise applications

Experience in retail, e-commerce, loyalty, customer service, or supply-chain environments

Experience with collaboration tools such as JIRA and Confluence

Personal Skills & Qualities

Self-motivated with a strong team spirit

Strong problem-solving and troubleshooting skills

Ability to work independently and collaborate effectively within a team

Comfortable working with evolving requirements and technologies

Strong sense of ownership and accountability

Ability to manage multiple priorities in a fast-paced environment

Ability to communicate AI concepts to technical and non-technical stakeholders

Commitment to building reliable, secure, and responsible AI solutions

TekStaff may use artificial intelligence (AI) tools as part of the applicant screening process. However, applications will also be reviewed by a member of our Recruitment team to ensure a fair and thorough assessment.