AI Engineer

Full-stack Engineer, AI Engineering & R&D: Associate/Senior Associate

At Factor, we take a discovery-led approach to the adoption and implementation of generative AI.  We’ve investing in our R&D capabilities to build “0-to-1" native generative AI accelerators that aim to augment our delivery teams, transform our core contracting services portfolio, and unlock value for our clients.

The Factor R&D team takes a deep, exploration-oriented approach to ensuring that solutions deployed for production use are reliable, accurate, and useful. We’re a small group, and entire pursuits/projects are typically worked on by individual contributors, with open dialogue and collaboration encouraged to facilitate the cross-pollination of ideas/approaches and distribute workloads. We provide access to leading AI code generation capabilities and tools to help speed up research, experimentation, and development, with the ability to provide additional resources if warranted.

We’ve leveraged everything from React and TypeScript/JavaScript for front-end and Python for the back-end for work in the past, but also utilize Office add-ins and more basic Streamlit interfaces where it makes sense. We have even built some prototypes entirely using custom GPTs! Most of the team haven’t mastered all these technologies, and we recognize that. But we also believe that it is entirely possible to learn through action and execution, as it has been our lived experience. The R&D team consists of a mix of talent, some with technical software development experience, and others without, but we are all capable of getting technical when we need to.  We use the stack that makes sense for each endeavour, driven primarily by usefulness to our teams and clients.

Full disclosure: we are not set up like a traditional development organization and tend to steer away from introducing more structure than absolutely necessary.  This is obviously a trade-off, but we find that this allows us to iterate quickly and fail fast, which ultimately leads to better execution. We see this as core to our culture, which favours individuals who are comfortable with uncertainty to a degree (we tend to pivot quickly when things don’t work) and able to adapt easily.

If you believe that you do your best work within a traditional multi-layered product organization with clear separation of responsibilities across product, UX, development, and engineering, this opportunity may not be the right fit for you. However, if you think you’d thrive in an environment that incentivizes exploration and favours the ability to learn and iterate quickly, then we’d love to chat.

Responsibilities:

• Work with R&D and delivery stakeholders to design and develop full-stack accelerators and AI-powered capabilities using appropriate technologies.
• Engage with users to understand problem/opportunity hyperspace within the scope of contract negotiation workflows.
• Review and implement cutting-edge techniques described in applied AI research, including but not limited to novel chunking, reranking, and search approaches.
• Integrate and implement generative AI capabilities surfaced across the communication layer, including web applications and Office add-ins.
• Support and maintain deployed accelerators; work with users to refine capabilities.
• Collaborate with UI/UX designers/other stakeholders to create intuitive interfaces for web apps and Office add-ins.
• Participate in code reviews and provide constructive feedback.

Essential Criteria:

• A deep understanding of generative AI and adjacent tools and frameworks.
• General proficiency in React and TypeScript/JavaScript, Python, and other languages/frameworks.
• Ability to iterate, experiment, and make high-quality design/development decisions quickly.
• Solid understanding of core generative AI prompting techniques and strategies.
• Familiarity with APIs exposed by frontier model providers.
• Familiarity with cloud platforms and infrastructure (Azure).
• General understanding of DevOps practices and CI/CD pipelines.
• Excellent communication skills and ability to work in a fast-paced, collaborative environment.

Desired Criteria:

• Knowledge of OAuth 2.0 and secure authentication practices
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes)
• Demonstrated experience utilizing or leveraging skills listed above in native AI solutioning, especially in the broader legal services on contracting space.
• Contributions to open-source projects