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Part Time Prompt Engineering Jobs in Ontario (NOW HIRING)

Tech Lead, AI Engineering

Toronto, ON · Hybrid

CA$75K - CA$141K/yr

Develops and applies Context engineering and Prompt engineering strategies , evaluation frameworks ... Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For ...

Part Time Prompt Engineering information

What is part time prompt engineering?

Part time prompt engineering refers to working on designing, testing, and refining prompts for artificial intelligence systems, such as large language models, on a part-time basis. Prompt engineers help improve how AI models understand and respond to user inputs by crafting effective instructions or questions. This role typically involves collaborating with teams to optimize AI outputs for specific tasks or applications. Part time positions allow for flexible work schedules, making it suitable for students or professionals seeking supplemental income.

What are the key skills and qualifications needed to thrive as a part time prompt engineer?

To thrive as a Part Time Prompt Engineer, you need a solid understanding of natural language processing (NLP), creativity in language design, and familiarity with AI model behavior, often supported by a background in computer science or linguistics. Proficiency with tools like OpenAI APIs, prompt testing platforms, and version control systems (e.g., Git) is important, and certifications in AI or data science can be advantageous. Strong analytical thinking, attention to detail, and effective communication help in refining prompts and collaborating with cross-functional teams. These combined skills ensure prompts are clear, effective, and aligned with intended outcomes, resulting in optimal AI model performance.

What are some common challenges faced in a part time prompt engineering role, and how can they be managed effectively?

Part-time prompt engineers often need to quickly adapt to changing project requirements and work with limited context compared to full-time counterparts. Balancing multiple tasks within reduced hours can make it challenging to stay updated on the latest AI model developments and best practices. To manage these challenges, effective time management, clear communication with the team, and utilizing collaborative tools are essential. Regularly reviewing project documentation and participating in knowledge-sharing sessions can also help part-time prompt engineers stay aligned with team goals and maintain high-quality outputs.

What is the difference between Part Time Prompt Engineering vs Part Time Data Annotation?

AspectPart Time Prompt EngineeringPart Time Data Annotation
Required CredentialsBasic understanding of AI, NLP, and prompt designAttention to detail, basic data labeling skills
Work EnvironmentRemote or office-based, tech-focusedRemote or on-site, data labeling platforms
Employer & Industry UsageAI companies, tech startups, research labsData companies, AI training firms, machine learning teams
Search & Comparison IntentUnderstanding prompt design roles, freelance or part-time workData labeling tasks, annotation jobs, training data creation

Part Time Prompt Engineering involves designing and refining prompts for AI models, requiring some knowledge of NLP and AI concepts. In contrast, Part Time Data Annotation focuses on labeling data to train AI systems, emphasizing attention to detail. Both roles are common in AI development but differ in skills and daily tasks.

What are popular job titles related to Part Time Prompt Engineering jobs in Ontario?

For Part Time Prompt Engineering jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Part Time Prompt Engineering jobs in Ontario look for?

The top searched job categories for Part Time Prompt Engineering jobs in Ontario are:

Infographic showing various Part Time Prompt Engineering job openings in Ontario as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Tech Lead, AI Engineering

Toronto, ON • Hybrid

CA$75K - CA$141K/yr

Full-time, Part-time

Medical, Life, Retirement

Re-posted 17 days ago


Job description

Application Deadline:

08/30/2026

Address:

33 Dundas Street West

Job Family Group:

Technology

Please note this role is HYBRID (2-3 days/week in the office)

Develops scalable, secure, and intelligent cloud-based AI applications with a focus on Agentic AI systems, Retrieval-Augmented Generation (RAG), and enterprise LLM integration. Leads the design, development, enhancement, testing, debugging, and maintenance of AI-driven cloud applications, and enables the transformation of business processes through AI automation and intelligent decisioning.

Applies deep expertise in cloud-native AI architectures, large language models, vector databases, and modern development frameworks to deliver enterprise-grade solutions in an Azure environment. This role combines strong hands-on technical capability with leadership to drive innovation and ensure alignment with financial industry standards, risk frameworks, and regulatory requirements.

Roles and Responsibilities

  • Designs, develops, and maintains AI-driven cloud applications using Python and modern AI frameworks
  • Leads the implementation of Agentic AI systems, including multi-agent orchestration and autonomous workflows
  • Builds and optimizes RAG pipelines, including embeddings, vector databases, and retrieval strategies
  • Integrates data from multiple sources (structured and unstructured) while addressing security, compatibility, and governance risks
  • Maintains AI applications and infrastructure to ensure scalability, performance, and reliability
  • Develops and applies Context engineering and Prompt engineering strategies, evaluation frameworks, and model optimization techniques (e.g., fine-tuning, LoRA, embeddings)
  • Establishes CI/CD pipelines, development environments, and MLOps/LLMOps practices to support AI solution delivery
  • Creates technical documentation, development standards, and operational procedures
  • Translates business requirements into AI-enabled technical solutions, collaborating with stakeholders across business and technology teams
  • Provides technical leadership, mentorship, and delivery guidance to engineering teams
  • Serves as a specialist resource to senior leaders and stakeholders, works independently and leads delivery across complex, non-routine initiatives
  • Supports enterprise AI strategy and contributes to broader innovation and transformation initiatives
  • Applies strong judgment to identify and resolve complex technical issues, including LLM performance, scalability, guardrails (RAI/RAIOps), and integration challenges
  • Ensures alignment with BMO's Risk Management Framework, including responsible AI usage, data privacy, and regulatory compliance

Qualifications:

Experience & Education

  • University degree in Computer Science, Engineering
  • 8+ years of experience in software engineering, cloud platforms and distributed systems
  • 2+ years of AI/ML engineering experience, with strong recent hands-on experience in LLMs and generative AI (e.g., RAG, agentic AI, prompt/context engineering)

Technical Expertise

  • Advanced proficiency in:
    • Python / NodeJS / Java and AI/LLM frameworks (e.g., Semantic Kernel / MAF, LangChain, LlamaIndex, FastAPI)
    • Cloud platforms (Azure preferred; AWS acceptable), CDKTF
    • API development, microservices, and distributed systems
    • Agentic AI frameworks and architectures
    • RAG design patterns and vector databases
  • Strong understanding of:
    • LLM fundamentals (transformers, embeddings, tokenization)
    • Model evaluation, performance monitoring, observability, and AI guardrails (Responsible AI / RAIOps)
    • Cloud security, data privacy, AI governance, and compliance frameworks

Core Capabilities

  • Strong leadership and mentoring skills
  • Proven ability to lead large-scale, complex technical initiatives end-to-end
  • Delivery leadership mindset with strong execution and ownership
  • Excellent problem-solving and analytical skills
  • Strong communication and stakeholder management skills
  • Deep understanding of SDLC, cloud architecture, and enterprise application development

Nice to Have

  • Experience in financial services / banking / wealth management
  • Experience leading enterprise-scale AI transformation initiatives
  • Relevant certifications:
    • Microsoft Azure AI Engineer / Solutions Architect
    • AWS Machine Learning / Solutions Architect

Salary:

$75,900.00 - $141,900.00

Pay Type:

Salaried

The above represents BMO Financial Group's pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit:https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other's differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.