Job Description & How to Apply Below
You deserve an awesome career! At Execulink, you'll join a team of talented individuals who feel like family and support your growth and career goals. As we rapidly grow, we continue our unwavering commitment to live and breathe our Vision, Mission and Values. While enhancing life at home, work and play, we continue to grow our team with innovative individuals who are as excited about creating an awesome experience for our customers as we are!
Overview About this Opportunity:
Are you an AI enthusiast ready to make a real impact? Execulink Telecom is seeking a talented AI Engineer to join our team in Woodstock, Ontario. In this exciting role, you’ll design and build advanced AI systems—think RAG pipelines, LLM-powered applications, and agentic workflows—that transform business challenges into smart solutions.
You’ll collaborate across teams, leverage the latest AI frameworks, and deploy scalable, production-ready models that drive measurable results. If you’re passionate about innovation, love tackling complex problems, and want to be part of a forward-thinking company, this is the opportunity for you.
Join us and be a key player in shaping the future of AI-powered telecom!
Woodstock, ON
Permanent, Full Time
Hours of Work
Monday to Friday 8:30am – 5:00pm
Hybrid role opportunity
Required to work in office a minimum of 3 days per week
Ability to work flexible hours outside of regular office hours may be required for maintenance activities
Responsibilities:
Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines that ground LLM responses in enterprise knowledge
Develop and maintain agentic workflows and orchestration systems for multi-step reasoning and tool use
Build and deploy machine learning models that solve real-world business challenges including predictive and classification problems
Integrate LLMs and AI agents with APIs, databases, and enterprise applications
Prepare and transform datasets for model training, testing, and validation
Implement monitoring, evaluation, and guardrails for production AI systems
Collaborate with data engineering and infrastructure teams to ensure scalability and performance optimization
Research and evaluate emerging AI frameworks, vector stores, and tools to continuously improve system capabilities
Contribute to best practices in AI security, data privacy, and prompt engineering
HR Responsibilities:
None
Qualifications:
3-6 years of software engineering experience, ideally in backend, ML, or data-intensive systems
Bachelor's degree in Computer Science, Data Science, Engineering, or related field
Strong programming skills in Python and experience with ML frameworks (Tensor Flow, PyTorch, scikit-learn, or similar)
Hands-on experience with LLM application development including RAG pipelines, embeddings, and vector databases
Proficiency in SQL and understanding of data preprocessing, model validation, and performance metrics
Experience with cloud platforms (Azure preferred) and hybrid cloud/on-premises infrastructure
Understanding of containerization (Docker/Kubernetes) and microservices architecture
Knowledge of prompt engineering, model evaluation, and production AI best practices
Experience in Postgre
SQL and PGVector or similar Vector / Relational DBs
Experience with structured data vector parsing, Dev Ops CI/CD Pipelines
Experience with agent orchestration frameworks (Lang Chain, Llama Index, Semantic Kernel, DSPy, or similar) is preferred
Familiarity with vector database implementations (pgvector preferred) is considered an asset
Knowledge of MLOps tools, automated pipelines, and AI observability platforms is preferred
Experience with MCP (Model Context Protocol) or multi-agent systems is considered an asset
Background in information retrieval, search ranking, or knowledge graphs is preferred
Required Skills & Abilities:
Strong problem-solving skills with ability to design solutions for complex technical challenges
Excellent coding practices with focus on performance, scalability, and maintainability
Ability to translate business requirements into technical implementations
Strong communication skills for…
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