Staff Software Developer – AI Products

Safe Software

. Take a leading technical role in the FME AI Service, AI Assist Plugin, and future AI product offerings .

Posted 9/29/2026full-timeCanadaLead💰 CA$147,200 - CA$160,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and building server-side services and APIs using FastAPI, with a strong background in LLM-based applications and statistical literacy. Capable of leading technical decision-making processes and collaborating effectively with cross-functional teams to enhance AI product offerings.

Highest-signal resume keywords

FastAPI DevelopmentLLM-Based ApplicationsStatistical LiteracyBackend Systems ExperienceDocker and Kubernetes Deployment

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Backend Programming LanguageAgentic WorkflowsUnit and Integration TestingCode ReviewLLM Evaluation LibrariesLLM Observability ToolsData IntegrationStatistical AnalysisEmbedding KnowledgeSecurity Vulnerabilities Understanding

Soft Skills

Organizational SkillsResourcefulnessTeam CollaborationTechnical CommunicationEmpirical Mindset

Tools & Technologies

AWSGCPAzureDockerKubernetesLangSmithLangfuseBraintrustArize PhoenixFME

Industry Keywords

Machine LearningData ScienceETL ToolsSpatial Data ProcessingOWASP Top 10

Tech Stack

Tools & technologies

AWSAzureDockerETLGoogle Cloud PlatformKubernetes

About the role

Key responsibilities & impact

Take a leading technical role in the FME AI Service, AI Assist Plugin, and future AI product offerings
Design and build server-side services and APIs using FastAPI
Design and build modular agentic workflows to augment FME platform capabilities
Stay current with AI and LLM tooling and incorporate relevant ideas into products
Participate in the full development cycle, including specifications, coding, unit and integration testing, code reviews, and maintaining existing code
Collaborate, support, and share expertise with team members
Work with product owners and design teams to deliver a high-quality, consistent user experience
Maintain and improve the AI service build and delivery process to reduce query latency and improve assistant response quality
Investigate, evaluate, and resolve anomalies and bugs in live applications
Participate in the team's light on-call rotation
Participate in agile team meetings, including stand-ups and planning
Lead technical decision-making processes
Work with Product Managers, UX Designers, QA, and Customer Experience team members reviewing live AI application traces

Requirements

What you’ll need

Bachelor's degree in Computer Science or a related field, or equivalent experience
Typically, at least 7 years of experience working on production backend systems
Track record of leading technically ambiguous projects and raising the capability of engineers
Project or work experience with agentic LLM-based applications, including RAG, prompt and context engineering, and tool calling
Experience evaluating LLM systems by building eval sets, defining quality metrics, and tracing and debugging non-deterministic behaviour
Depth in at least one modern backend language and ability to learn others
Experience with a modern backend web framework such as FastAPI
Empirical mindset and comfort designing and running experiments
Strong interest in the craft and eagerness to learn new tools and technologies
Ability to explain technical tradeoffs clearly
Excellent organizational skills and ability to prioritize work
Resourcefulness and ability to work well in a team-based environment
Familiarity with LLM evaluation libraries such as Ragas, DeepEval, openevals, promptfoo, Inspect, or TruLens
Experience with LLM observability and tracing tools such as LangSmith, Langfuse, Braintrust, or Arize Phoenix
Statistical literacy including A/B testing, significance, and sample sizing
Background in machine learning or data science, or close collaboration with those practitioners
Experience with FME, ETL tools, spatial data processing, or data integration
Working knowledge of embeddings, vector databases such as pgvector, and chunking and retrieval strategy
Experience with Docker and deploying applications on Kubernetes
Experience with AWS, GCP, or Azure services
Understanding of OWASP Top 10 and security vulnerabilities specific to LLM-based applications
Ability to participate in a light on-call rotation
Legally eligible to work in Canada

Benefits

Comp & perks

Paid time off to volunteer for Safe-organized opportunities
Annual learning budget
Training programs paid for by Safe
Flexible and remote-friendly work arrangements
3 weeks of vacation
Additional paid 6 seasonal days off per year
Extended health benefits from day 1
Dental benefits from day 1
Health or lifestyle spending benefits from day 1
Counseling benefits from day 1
Parental Leave Top-Up Program
Bi-annual profit sharing
RRSP/TFSA matching program
Complimentary parking
Bike storage