Mid-Level Software Engineer – Agentic AI

Job Summary

We are seeking a talented Mid-Level Software Engineer – Agentic AI to join our growing engineering team and help design, develop, and scale intelligent software systems powered by artificial intelligence and machine learning.

This role is ideal for a software engineer with strong development fundamentals who is interested in building AI-powered applications, agentic workflows, and scalable systems that can reason, make decisions, use tools, and automate complex processes. The successful candidate will work closely with software engineers, data scientists, product managers, and other technical stakeholders to develop secure, reliable, and production-ready AI solutions.

The ideal candidate is a strong problem solver who is comfortable working in a fast-moving environment, enjoys experimenting with emerging technologies, and can translate complex technical challenges into practical solutions.

Key Responsibilities

Agentic AI & Software Development

- Design, develop, test, and maintain scalable software applications incorporating AI and machine learning capabilities.
- Build and integrate AI agents capable of reasoning, planning, tool use, workflow execution, and task automation.
- Develop reliable agentic workflows using large language models, APIs, databases, external tools, and other software services.
- Integrate AI capabilities into existing applications, platforms, and internal systems.
- Develop reusable services, APIs, libraries, and components that support AI-powered products and workflows.
- Evaluate emerging AI technologies and identify opportunities to improve product capabilities and engineering efficiency.

AI & Machine Learning Integration
- Collaborate with data scientists and machine learning engineers to integrate models into production applications.
- Work with large language models, prompt engineering, retrieval-augmented generation (RAG), embeddings, vector databases, and related AI technologies.
- Develop approaches for improving AI system accuracy, reliability, latency,



and scalability.
- Design evaluation processes and metrics to assess the performance of AI-powered applications and agents.
- Monitor AI system behavior and identify opportunities for continuous improvement.

Software Engineering & Architecture
- Write clean, maintainable, well-tested, and production-quality code.
- Participate in architecture discussions and contribute to technical design decisions.
- Optimize application performance, reliability, scalability, and resource utilization.
- Troubleshoot complex software issues and participate in root-cause analysis.
- Develop automated tests and contribute to CI/CD and deployment processes.
- Maintain technical documentation covering system architecture, APIs, workflows, and implementation decisions.

Security & Reliability
- Apply secure software development practices throughout the development lifecycle.
- Help protect sensitive data and ensure AI applications follow appropriate security and privacy standards.
- Identify potential vulnerabilities, failure modes, and reliability risks in AI-powered systems.
- Implement appropriate monitoring, logging, validation, and safeguards for production AI applications.
- Contribute to responsible AI practices, including appropriate human oversight and evaluation of model outputs.

Collaboration & Technical Leadership
- Work closely with product, engineering, data science, and other cross-functional teams to deliver business-focused solutions.
- Participate in code reviews, technical discussions, sprint planning, and engineering design sessions.
- Provide technical guidance and mentorship to junior engineers when appropriate.




- Communicate technical concepts clearly to both technical and non-technical stakeholders.
- Contribute to engineering standards, development practices, and continuous improvement initiatives.

Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field.
- 3–5 years of professional software engineering experience.
- Strong proficiency in at least one up-to-date programming language, such as Python, Java, JavaScript/TypeScript, Go, or C .
- Experience developing scalable web applications, APIs, backend services, or distributed systems.
- Practical experience integrating AI or machine learning capabilities into software applications.
- Familiarity with large language models and generative AI technologies.
- Understanding of APIs, databases, cloud services, software architecture, and modern development practices.
- Strong understanding of software testing, debugging, version control, and CI/CD practices.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills.

Preferred Qualifications
- Experience building agentic AI applications or autonomous AI workflows.
- Experience with LLM orchestration frameworks and agent development platforms.
- Experience with RAG architectures, embeddings, vector databases, and semantic search.
- Experience with AI evaluation, observability, monitoring, or model performance optimization.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
- Experience with machine learning frameworks or libraries such as PyTorch, TensorFlow, or scikit-learn.
- Experience with prompt engineering and structured output techniques.
- Knowledge of cybersecurity, data privacy, and responsible AI principles.
- Experience working in fintech, identity, fraud prevention, cybersecurity, or other data-intensive environments is a plus.

📌 Agentic AI Mid-Level Software Engineer (Toronto)
🏢 Frederick Fox
📍 Toronto