Senior Applied AI Engineer - Clariti

About Clariti

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.

The Role

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. You will 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.

Key Responsibilities

• Own computer vision and agentic AI problem domains, selecting and adapting architectures and training/fine-tuning strategies for complex, unstructured real-world data.
• Drive the design and execution of experiments end to end, from framing questions to evaluating model performance and determining implementation paths.
• Help shape technical direction by identifying high-impact opportunities to improve AI systems using applied experience and practical judgment.
• Make pragmatic trade-offs across model accuracy, interpretability, latency, and cost, owning decisions directly with stakeholders.
• Share experience with research teammates and 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 — bringing practical advances into production.
• Partner with product and engineering managers across Clariti to identify high-value AI opportunities for customers.

Requirements

• 7–10 years of hands-on experience in applied AI/ML in industry, with a track record of shipping models that solve real business problems.
• Demonstrated experience as the lead or sole AI expert on a project, taking work from proof of concept to production independently.
• Hands-on fluency with MLOps practices and infrastructure, including CI/CD for models, containerization, deployment, and monitoring.
• Proven ability to operate independently within cross-functional teams alongside product managers, engineering managers, and nontechnical stakeholders.
• Strong experience building production agentic AI workflows and LLM-powered applications, including retrieval, tool use, evaluation, and guardrails.
• Deep experience training and fine-tuning models with modern frameworks (defining architectures, curating datasets, tuning parameters, and diagnosing performance).
• Significant experience with computer vision and image processing (feature extraction, object detection, segmentation, and geometric transformations).
• Familiarity with diffusion models, model distillation, or multimodal architectures in production.
• Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Hands-on experience with end-to-end ML workflows on cloud platforms (AWS, Azure, or GCP).
• Solid software engineering fundamentals, including Git, testing, API design, and modular code development.
• Excellent communication skills to align stakeholders, justify technical trade-offs, write clear design proposals, and explain AI concepts across teams.

Bonus Points

• Experience in a forward-deployed, embedded, or solutions engineering role.
• Experience building high-accuracy computer vision systems under strict tolerances (e.g., autonomous vehicles, medical imaging, or industrial inspection).
• Comfort thriving in an early-stage or startup environment.
• Interest in ethical AI development and responsible AI design.
• Exposure to construction, civic-tech, or regulatory/compliance domains.

Additional Details

• Background Checks: All successful candidates must undergo comprehensive background checks focusing on global sanctions and criminal offences relevant to employment.
• Travel: Remote-first setup with occasional travel required for company-wide or departmental offsites, typically 1–2 times per year.