AI Developer Senior

Pay at Intact is about much more than just salary.

Flexible work arrangements and a hybrid work model

Possibility to purchase up to 5 extra days off per year

Multiple benefits offered to support physical and mental wellbeing, including telemedicine, Wellness account and much more

Share plan & other savings : up to 12% of salary or even more (ask how you could earn guaranteed income for life)

Salary range (but not limited to) :

118,700 - 145,100

Annual bonus target, based on the base salary, with a potential payout of up to double the target (subject to personal and company performance) :

12%

As part of our commitment to Win As A Team , we share our success with employees through our annual bonus plan and Employee Share Purchase Plan (ESPP) – with Intact matching 50% of your net shares.

Our pension offerings provide flexibility and long-term security for our employees beyond their careers. We are one of the few companies offering the opportunity to receive guaranteed income for life via our defined benefit pension plan.

Salary for the candidate will be determined taking into consideration a number of factors including : experience, skills, qualifications, anticipated contribution to role, internal equity, etc. The salary range presented above is based on a 35-hour workweek and would represent a majority of different candidate profiles. However, we encourage candidates who may fall outside of this range to apply as well.

About the role

We’re looking for someone to join a dynamic and innovative team to build production-grade AI systems that help boost velocity across Software Engineering, Infrastructure, Security, and IT Services teams. You’ll design agentic automations, leveraging access to data and tools, to drive productivity enhancements -grounded in safety, reliability, and measurable impact. This role blends hands-on building with platform thinking; creating and shipping capabilities that other teams can adopt and extend.

Key Responsibilities :

Partner with domain teams to identify high-ROI use cases.

Prototype, build, and own production ready (scalable, observable, secure) AI solutions, leveraging leading LLMs and Agentic AI platforms

Drive adoption of solutions through demos and user training.

Improve productivity throughout the entire SDLC process with AI solutions, from Requirements and Design phase to Coding and Testing to Deployment and Runtime Operations.

Improve AI-driven testing, troubleshooting, incident triaging, root cause analysis, and automation of repetitive workflows with verifiable outcomes.

Build agentic automation, orchestrate multi-step workflows that plan tasks, call tools / APIs, and execute autonomously with clear guardrails.

Implement RAG pipelines, ingest documents, create embeddings, index vectors, retrieve and rerank results, and ground outputs with citations.

Develop system prompts, templates, and structured outputs (e.g., JSON) with versioning and evaluation.

Set up tracing, relevance / factuality evaluations, and dashboards for cost, latency, and quality metrics.

Contribute to best practices, patterns, and internal enablement materials.

Core Competencies :

Agent frameworks : Hands-on experience with frameworks such as LangChain / LangGraph, CrewAI, ADK, and AgentFlow for scalable agent workflows.

Experience with designing interfaces, MCP integration, context engineering, long / short memory, planning, and control flows.

LLM integration : Experience building with Vertex AI / Gemini, AWS Bedrock, OpenAI, and Anthropic APIs.

Retrieval expertise : Embeddings, vector databases (Pinecone, Weaviate, Milvus, pgvector), hybrid search, and reranking.

Observability, caching, batching, and token budgeting for performance.

SDLC excellence : Strong software engineering practices with AI-driven design, testing, and CI / CD integration.

Practical experience with cloud providers, identity / permissions, secrets, reliability, Kubernetes / serverless, message queues, and various common cloud capabilities.

Qualifications :

7+ years in software engineering, data / ML engineering, or platform engineering; 2+ years building solutions with LLMs.

Proficiency in Java, Python, and / or TypeScript; experience building production services and integrations.

Excellent knowledge of cloud platforms (GCP / AWS), containerization (Docker / Kubernetes), and modern CI / CD.

Strong communication skills and a product mindset—able to translate operational pain points into robust solutions.

For candidates located in Quebec, bilingualism is required considering the necessity to interact on a regular basis with English-speaking colleagues across the country.

No Canadian work experience required however must be eligible to work in Canada.

#LI-Hybrid

Il s'agit d'un nouveau rôle au sein de notre équipe en plein croissance | This role is a new member of our growing team.