Lead and coach multiple development teams to deliver SDLC solutions for an LLM-enabled insurance quoting prototype. Define methodologies, technology choices, and testing automation (functional and non-functional). Drive development lifecycle products across design, code, testing and operations while applying best practices in development, data, and security. Represent teams to senior management, document frameworks, mentor developers, and stay current on technological trends. English level: Intermediate.
Project
context: The objective is to demonstrate the ability of distribution tools
built on the Genesis platform (EIS) to interact with a large language model
(LLM) or agentic AI in a real-world data collection context for generating
insurance quotes. The targeted process is auto insurance quotes in Quebec for
the Insurance brand.
Main
responsibilities
- Coach
several teams in the application of technologies for developing business
solutions and help them progress in order to improve delivery velocity.
- Identify
and prioritize development cycle optimization projects to support business
strategies.
- Ensure the
analysis and development of software development lifecycle support products,
including, if required, design, code, testing, and operations, while applying
best practices in development, data, and security.
- Define, in
collaboration with the software architecture team, development methodologies,
development patterns, and technology choices, and share them across the teams
you lead.
- Ensure the
automation of testing for both functional and non-functional requirements
(mastering associated methodologies; e.g., test pyramids, TDD, BDD,
load/performance, security, etc.).
- Represent
the teams to various members of senior management and to internal/external
partners and organizations.
- Stay
current on technological trends and development practices, and act as a mentor
to development teams regarding technologies and best practices.
- Establish
frameworks, experiment with, and document technical solutions and practices to
ensure the sustainability of development lifecycle support products. English
level: Intermediate
Requirements
The
following will be considered an asset:
- Knowledge
of AI concepts and tools
- Knowledge
of Genesis/Amber (software package from the EIS vendor)
- Knowledge
of DGAG (Auto solutions)
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What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
