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Data Annotation For Ai Jobs in Manitoba (NOW HIRING)

ALS

Junior Machine Learning Engineer

Winnipeg, MB · On-site

CA$80K - CA$95K/yr

You will work with data scientists, engineers, product teams, and business stakeholders to help transform ideas into scalable AI-enabled products and workflows. This role is well suited for someone ...

Cayenta

(Remote) Support Analyst

Winnipeg, MB · Remote

... data troubleshooting. * Experience using AI tools such as ChatGPT, Claude, Microsoft Copilot, or similar platforms for research, troubleshooting, analysis, documentation, or productivity is an asset.

Harris

(Remote) Support Analyst

Winnipeg, MB · Remote

... data troubleshooting. * Experience using AI tools such as ChatGPT, Claude, Microsoft Copilot, or similar platforms for research, troubleshooting, analysis, documentation, or productivity is an asset.

Harris

(Remote) Support Analyst

Winnipeg, MB · Remote

... data troubleshooting. * Experience using AI tools such as ChatGPT, Claude, Microsoft Copilot, or similar platforms for research, troubleshooting, analysis, documentation, or productivity is an asset.

People Corporation

Retirement Analyst

Winnipeg, MB

Produce recurring and ad-hoc reports for client reviews, internal leadership, and new business opportunities * Leverage AI tools to automate reporting processes and enhance data visualization

Yee Hong Centre for Geriatric Care

CA$17.70 - CA$20.82/hr

Complies with risk management policy for health and safety and data security * Keeps up-to-date ... Our hiring process involves the use of Artificial Intelligence (AI) to assist with screening of the ...

Influence Marketing

Sales Specialist

Winnipeg, MB

CA$25/hr

The listed salary range reflects what the company is willing to pay for this role, based on skills, experience, and market data. AI Disclosure Use of Artificial Intelligence by Recruiters and Hiring ...

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Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What are popular job titles related to Data Annotation For Ai jobs in Manitoba?

For Data Annotation For Ai jobs in Manitoba, the most frequently searched job titles are:

What job categories do people searching Data Annotation For Ai jobs in Manitoba look for?

The top searched job categories for Data Annotation For Ai jobs in Manitoba are:

Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Manitoba as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 79% Physical, 4% Hybrid, and 17% Remote job distribution.

Senior AI Architect - Direct to Market

Wawanesa Insurance

Winnipeg, MB • Hybrid

CA$130K - CA$165K/yr

Full-time, Part-time

Retirement, PTO

Posted 28 days ago

Job description

Job ID: 10169 


Employment Type: Existing Role 

Work Environment: We offer a hybrid work environment that offers flexibility to our employees in balancing in-office (2 days per week OR 15 hours per week in a Wawanesa office) and remote work. You may work from any of the following locations: Winnipeg, MB; Calgary, AB; Toronto (North York), ON.

Working Business Language: English 
 

Salary: At Wawanesa, salary is only one component of a holistic, comprehensive and competitive offering that we provide to our employees. In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus plan, leave of absence top-up programs and provided with generous vacation time, personal days, premium free benefits and pension plan. 
 

The salary offered for this role is determined with consideration to various factors, including but not limited to: your work location, local labour market conditions, external market salary data, internal pay equity and the knowledge, skills, experience and anticipated proficiency in the role. The salary offered is estimated to be within the following range: $130,000 - $165,000. Candidates with salary expectations outside of the range are still encouraged to apply. 

About The Wawanesa Mutual Insurance Company
Founded in 1896, The Wawanesa Mutual Insurance Company is one of Canada's largest mutual insurers, 100% owned by its members, with more than $4.1 billion in annual revenue and $12.5 billion in assets. Headquartered in Winnipeg, Wawanesa is the parent company of Wawanesa Life, which provides life insurance solutions throughout Canada, and Western Financial Group, a leading national distributor of personal and business insurance. In March of 2026, Wawanesa entered into an agreement to acquire Everest Insurance Company of Canada to strengthen its commercial insurance capabilities and advance its long-term growth strategy.


Wawanesa proudly serves more than 1.8 million members and we are home to more than 3,000 employees across Canada. The company actively gives back to organizations that strengthen communities, donating more than $4 million annually to charitable organizations, including more than $2 million each year in support of people on the front lines of climate change. Learn more at wawanesa.com.

We are currently looking for dedicated, driven, and enthusiastic individuals who thrive in an environment that welcomes change and are looking for an opportunity for diverse experience and advancement on a growing team.

Job Overview

Responsible for designing and evolving the agentic AI platform capabilities that power Direct 2 Market (D2M) interactions across voice, messaging, and digital channels. D2M is a strategic venture to build Wawanesa's digitally native distribution model, reimagining how members (customers) discover, quote, buy, and manage insurance through AI-first experiences. 

This role brings agentic experiences to life by combining hands-on technical depth with architectural leadership across LLM-driven workflows, orchestration, memory, tool use, model access, and human-in-the-loop operations. It sits at the intersection of AI, experience, and platform, ensuring agentic capabilities are not just prototyped, but integrated into cohesive, scalable, secure, production-ready enterprise solutions that support end-to-end member journeys. This role is deeply embedded in an AI-first delivery model, acting as a technical leader for how agentic capabilities are shaped, implemented, evaluated, governed, and expanded over time. 

Job Responsibilities
  • Own the architecture and direction for agentic platform capabilities across voice, messaging, and digital channels, ensuring consistent underlying intelligence across interaction modes. 
  • Design multi-step agentic workflows that coordinate tools, APIs, and decisioning across the end-to-end member journey. 
  • Define how conversational state, memory, and context persist across interactions so members can move between AI and human-assisted journeys without losing continuity. 
  • Architect the cloud platform capabilities required for real-time agentic experiences, including speech, messaging, orchestration, knowledge retrieval, model access, and tool execution. 
  • Architect integrations with core enterprise systems and supporting platforms, including policy, billing, CRM/contact center, document generation, and third-party data services. 
  • Develop patterns for authorization, execution controls, auditability, explainability, observability, and progressive delegation of AI actions. 
  • Define the evaluation and quality framework, including golden datasets, regression tests, hallucination and safety evaluations, latency, and cost benchmarks for agents and RAG pipelines. 
  • Guide the development of pilots, prototypes, and reference implementations to validate new agentic capabilities through rapid test-and-learn cycles. 
  • Lead technical working sessions, design reviews, code reviews, and architecture discussions to align teams on patterns, trade-offs, and implementation decisions. 
  • Influence the broader enterprise agentic platform direction by contributing learnings, patterns, and reusable capabilities from D2M into the organization's shared agentic AI foundation. 
  • Partner with Data, Integration, Platform, Cybersecurity, and Governance Architects to align D2M agentic AI solutions with enterprise architectures, standards, and Responsible AI requirements. 
  • Contribute to Architecture Review Board, Technical Review Board, and Architecture Working Group forums, and author Architecture Decision Requests for significant D2M AI decisions. 
Qualifications
  • Bachelor's degree in Computer Science, Engineering, or a related discipline; graduate degree in AI/ML is an asset. 
  • 10+ years in enterprise solution, platform, or software architecture, including architecting or delivering production LLM, GenAI, or agentic AI applications. 
  • Demonstrates strong ownership of outcomes, direct communication, and willingness to challenge ideas constructively. 
  • Comfortable operating in a high-trust, fast-moving environment with emphasis on experimentation, accountability, and continuous learning. 
  • Deep experience designing and delivering LLM-powered applications, including conversational systems and agentic workflows, using modern frameworks such as LangGraph, LangChain, or Copilot Studio. 
  • Practical expertise in orchestration patterns, prompt and context engineering, RAG, vector databases, embeddings, evaluation approaches, and deployment at scale. 
  • Working knowledge of Model Context Protocol (MCP), tool/function calling, and modern agent-to-system interoperability patterns. 
  • Proven software engineering capability with experience building and deploying enterprise production systems. 
  • Experience integrating AI capabilities with enterprise systems, APIs, events, and operational platforms in complex environments. 
  • Strong cloud architecture and engineering knowledge (AWS preferred), including services that support real-time voice, messaging, orchestration, and scalable execution. 
  • Experience defining reference architectures, reusable platform capabilities, technical standards, and implementation patterns for enterprise AI solutions. 
  • Strong technical communication and facilitation skills, with the ability to explain architecture, trade-offs, and implementation patterns clearly to both technical and non-technical stakeholders. 
  • Experience working in AI-augmented or AI-first delivery environments is strongly preferred. 
  • Insurance, financial services, or other regulated-industry experience is an asset. 

#LI-JB3 #LI-HYBRID


Diversity Equity, Inclusion& Belonging
At Wawanesa, we are committed to Diversity, Equity, Inclusion and Belonging (DEIB) and believe that our strength lies in the diversity of our people - this is supported by having a representative workforce.

We welcome applications from all qualified candidates, including racialized persons, women, Indigenous Peoples, persons with disabilities, members of the 2SLGBTQIA+ community, gender-diverse and neurodiverse individuals, and anyone who can contribute to the further diversification of thought and ideas. 
 

We aim to ensure our recruitment process is accessible to all candidates. If you require accommodations during any stage of the recruitment process, please reach out in confidence to jobs@wawanesa.com.
 

All Wawanesa job applicants are subject to Wawanesa's Privacy Policy.

Please note that the recruitment process for this position may involve the use of AI tools to screen, assess, or select applicants. All final decisions are taken or reviewed by human recruiters and human hiring leaders in compliance with all applicable legislation.  
 

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