Senior Applied AI Engineer

Join our mission to provide governments with exceptional experiences so they can do the same for their communities!

We empower governments to deliver exceptional citizen experiences.

Check out our ‘About Us’page for a deep dive into our product and what makes us exceptional.

At Clariti, we empower public-sector teams with modern technology to streamline land use, permitting, and regulatory compliance - enabling safer, more efficient community development. Artificial intelligence drives the future of our product roadmap. Through CivCheck, we created Guided AI Plan Review™ (GPR) - a pioneering solution merging specialized domain knowledge with machine learning to simplify intricate building requirements for reviewers and applicants alike. Building on this success, we are now embedding intelligent workflows throughout our entire product suite, beginning with a complete AI-first evolution of our core enterprise offering.

We're seeking a Senior Applied AI Engineer to serve as a forward-deployed AI expert across Clariti's product teams. You'll turn the latest machine learning research into practical, production-ready features, spanning large language models (LLMs), agentic AI workflows, computer vision, and multimodal learning.

You'll report into our CivCheck AI Research team, the home of Clariti's AI expertise, but your day-to-day work will be embedded with product and engineering managers across the company. On these projects, you'll often be the AI specialist, bringing expertise in model selection, deployment, and agentic AI to bring brand-new capabilities in an AI-native transformation of Clariti’s existing products. That means you'll drive projects end to end: scoping the problem, building the proof of concept, and taking it all the way to production with our MLOps tooling and infrastructure. You'll bring your proposed approaches to the CivCheck AI Research team for design feedback, giving you a strong peer group for technical rigor while you own delivery within your product team.

The ideal candidate has spent years doing applied AI work in industry, is comfortable being the go-to AI person on a cross-functional team, and is energized by hard, open-ended problems in a lean, fast-moving environment.

• Own computer vision and agentic AI problem domains, selecting and adapting architectures and training/fine-tuning strategies for the best results on complex, unstructured real-world data
• Drive the design and execution of experiments end to end, from framing the question to evaluating model performance and deciding what's worth pursuing
• Help shape technical direction by identifying high-impact opportunities to improve our AI systems, drawing on applied experience and practical judgment
• Make pragmatic trade-off calls across model accuracy, interpretability, latency, and cost, and directly own decisions in communication with stakeholders
• Share your experience with research teammates and help raise the bar for experimental rigor in a collaborative environment
• Stay current on techniques, benchmarks, and tooling across computer vision, generative AI, NLP, and multimodal learning — and bring the useful ones into practice
• Embed with product teams across Clariti, partnering with product and engineering managers to identify where AI can create the most value for our customers

• 7–10 years of hands-on experience in applied AI/ML in industry, with a track record of shipping models and systems that solved real business problems
• Demonstrated experience as the lead or sole AI expert on a project, taking your own work from proof of concept through to production without relying on a dedicated ML engineering team
• Hands-on fluency with MLOps practices and infrastructure, including CI/CD for models, containerization, deployment, and monitoring
• A proven ability to operate independently inside cross-functional teams, working closely with product managers, engineering managers, and nontechnical stakeholders
• Strong experience building agentic AI workflows and LLM-powered applications in production, including retrieval, tool use, evaluation, and guardrails
• Deep, demonstrated experience training and fine-tuning models using modern frameworks, including defining architectures, curating and cleaning datasets, tuning training parameters, and diagnosing training and validation performance
• Significant experience with computer vision and image processing, including feature extraction, object detection, segmentation, and geometric transformations
• Familiarity with diffusion models, model distillation, or multimodal architectures in production
• Strong proficiency in Python and experience with PyTorch, TensorFlow, JAX, or similar deep learning frameworks
• Hands-on experience with end-to-end ML workflows on cloud platforms such as AWS, Azure, or GCP
• Strong software engineering skills, including Git, testing, API design, and modular code that integrates cleanly into existing products and that non-ML engineers can maintain
• Sharp experimental and statistical intuition; comfortable making decisions from messy, incomplete results and separating critical unknowns from nice-to-haves
• Excellent communication skills: you can align stakeholders, justify trade-offs, write clear design proposals, and explain AI concepts to engineers, executives, and customers alike

• Experience in a forward-deployed, embedded, or solutions engineering role, bringing AI into teams or products that didn't have it before
• Experience developing computer vision systems requiring high accuracy and reliability under strict tolerances — for example, in autonomous vehicles, medical imaging, or industrial inspection
• Preference for or comfort thriving in an early-stage or startup environment
• Interest in the ethical implications of AI technology and responsible AI development and design
• Exposure to the construction, building, civic-tech, or regulatory/compliance domains

We invest in and empower our team members with competitive compensation packages, well deserved time off and benefits to keep you and your family healthy! *

💰 The base salary range for this role is expected to be between $150,000- $180,000 CAD based on the candidate’s skills, experience, and qualifications while considering internal pay equity and our broader pay philosophy. 💰

If you have questions about compensation as we move through the process, we’re happy to discuss further.

*Benefits depend on employment type (full-time, part-time, contract, etc).

Background checks - Because our customers trust us with sensitive information, we require all successful candidates to undergo comprehensive background checks before joining our team. We focus strictly on global sanctions and criminal offences that are directly relevant to employment at Clariti, and follow all applicable privacy and human rights legislation.

Travel- Although we operate as a remote company, all roles are expected to participate in occasional travel for in-person company-wide or departmental meetings, typically 1-2 times per year. Additional travel requirements specific to the role, if any, will be outlined in the job description.

We're committed to building an inclusive culture where our team members take ownership over projects, tasks, and outcomes; bring a growth mindset to drive continuous learning and self-development; have the ability to communicate courageously in a direct but respectful way; and are customer-focused by keeping the customer at the heart of decision-making. It’s the diversity of our team that helps us make better decisions, by leveraging the diversity in thought & experience across to create impactful solutions as we explore new paths & challenges as we grow. We’re working to create a workplace and team that is as diverse as the communities we serve. We welcome and encourage candidates of all backgrounds to apply.

If you require accommodations in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in our hiring process for any reason, please direct your questions to and we’ll be happy to support you.

Originally posted on Himalayas