We are hiring a Senior AI Engineer to build and run production AI systems across this portfolio and help set the team's technical direction. This is a hands-on role: you own solutions end to end, from problem framing with domain experts through deployment and support.
What you will do:
• Own AI applications and reusable services end-to-end: prototyping, integration, production deployment, monitoring, and support.
• Build agents, multimodal applications, LLM workflows, and RAG pipelines using prompt design, tool calling, structured outputs, embeddings, and hybrid search.
• Turn messy inputs (datasheets, schematics, test logs, media, business data) into grounded AI capabilities, including the ingestion and parsing pipelines behind them.
• Integrate AI with engineering tools, manufacturing and test systems, and business applications via APIs and MCP servers, with proper validation, security, and human oversight.
• Apply classical ML where it fits (classification, anomaly detection, computer vision, audio processing), often on noisy or limited datasets, and deploy and monitor those models alongside LLM systems.
• Build repeatable evaluations and use them to improve accuracy, reliability, latency, and cost.
• Develop and operate Python services on Azure with PostgreSQL, Terraform, containers, CI/CD, and observability.
• Shape technical direction with the engineering manager: propose architectures, set reusable patterns, and evaluate new models and tooling.
• Collaborate with stakeholders to clarify requirements and priorities; mentor engineers through code and design reviews.
What you will bring:
• 5+ years of software engineering experience, including delivering and supporting production LLM applications beyond proof-of-concept.
• Strong Python and backend skills: API design, testing, debugging, and maintainable software.
• Hands-on experience with LLM APIs, prompt design, and tool-enabled agents (LangChain, LangGraph, or equivalents).
• Practical RAG experience: embeddings, vector and hybrid search, reranking, and measuring retrieval and answer quality.
• Solid ML fundamentals: data processing, feature engineering, model training and evaluation, and shipping non-LLM models to production using PyTorch, scikit-learn, NumPy, and pandas.
• Experience deploying cloud applications, preferably on Azure, with containers, CI/CD, infrastructure as code, and monitoring.
• Strong SQL skills, preferably PostgreSQL, and a working understanding of authentication, access control, and secure data handling.
• Clear communication of technical trade-offs to technical and non-technical audiences; able to contribute independently and mentor others.
If you meet most of these, we encourage you to apply.
Nice to have:
• AI or ML applied to manufacturing, hardware design, automated inspection or test, or audio/video processing.
• Multimodal models, computer vision, anomaly detection, or audio and signal processing.
• MCP server development, LLM observability tools (LangSmith, Langfuse), or model serving (vLLM, Ollama).
• Fine-tuning open-weight models; helping non-technical teams adopt AI tools.
• Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent experience.
Recruitment process:
- Screening with a recruiter (60 min)
- Interview with Hiring Manager (60 min)
- Technical interview with 2 Senior Engineers (60 min)
Skills Required
- 5+ years of software engineering experience
- Experience delivering and supporting production LLM applications beyond proof of concept
- Strong Python and backend development skills, including API design, testing, debugging, and maintainable software
- Hands-on experience with LLM APIs, prompt design, and tool-enabled agents such as LangChain or LangGraph
- Practical RAG experience with embeddings, vector or hybrid search, reranking, and retrieval and answer quality measurement
- ML fundamentals including data processing, feature engineering, model training, and model evaluation
- Production deployment of non-LLM models using PyTorch, scikit-learn, NumPy, and pandas
- Experience deploying cloud applications, preferably on Azure, with containers, CI/CD, infrastructure as code, and monitoring
- Strong SQL skills, preferably PostgreSQL
- Understanding of authentication, access control, and secure data handling
- Ability to communicate technical trade-offs to technical and non-technical audiences
- Ability to work independently and mentor other engineers
- AI or ML experience in manufacturing, hardware design, automated inspection or testing, or audio/video processing
- Experience with multimodal models, computer vision, anomaly detection, or audio and signal processing
- MCP server development, LLM observability tools, or model serving experience
- Experience fine-tuning open-weight models or helping non-technical teams adopt AI tools
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience
Evertz Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Evertz and has not been reviewed or approved by Evertz.
-
Healthcare Strength — Health and medical coverage, including dental and vision, along with employer-funded plans and an Employee Assistance Program with on-site counseling, are part of the package.
-
Retirement Support — A pension plan in Canada and a 401(k) with employer contribution in the U.S. are highlighted within the core offering.
-
Wellbeing & Lifestyle Benefits — Amenities such as an employee discount platform, recreational activities (e.g., sports teams, ping pong/pool tables), and a casual environment complement standard coverage.
Evertz Insights
What We Do
Evertz Microsystems (TSX:ET) is a leading global manufacturer of broadcast equipment and solutions that deliver content to television sets, on-demand services, WebTV, IPTV, and mobile devices (like phones and tablets). Evertz has expertise in delivering complete end-to-end broadcast solutions for all aspects of broadcast production including content creation, content distribution and content delivery. Considered as an innovator by their customers, Evertz delivers cutting edge solutions that are unmatched in the industry in both hardware and software. Evertz delivers products and solutions that can be found in major broadcast facilities on every continent. Evertz’ customer base also includes telcos, satellite, cable TV, and IPTV providers. With over 1700 employees, that include hardware and software engineers, Evertz is one of the leaders in the broadcast industry. Evertz has a global presence with offices located in: Canada, United States, United Kingdom, Germany, United Arab Emirates, India, Hong Kong, China, Singapore, and Australia. Evertz was named one of Canada’s 50 Best Managed Companies, which recognizes excellence in Canadian-owned and Canadian-managed companies. Canada’s 50 Best Managed Companies identifies Canadian corporate success through companies focused on their core vision, creating stakeholder value and excelling in the global economy
