[Remote] AI Software Engineer, Senior

Note: The job is a remote job and is open to candidates in USA. Cayuse Holdings is looking for a Senior AI Software Engineer to advance enterprise AI initiatives by transforming proof-of-concept solutions into scalable web applications. The role involves developing production-grade AI/ML services, collaborating with cross-functional teams, and ensuring compliance with enterprise standards.

Responsibilities

• Design, develop, and maintain production‑grade AI/ML services and web applications that extend existing POC solutions into scalable, secure, and reliable enterprise platforms
• Implement and optimize AI/ML workflows for: Model ingestion and lifecycle management, Automated quantity extraction from plans and documents, Plan conformance and rules‑based checks, Computer vision–based asset detection and inspection, NLP/LLM‑based plan review automation and document analysis
• Build secure, user‑friendly web interfaces and APIs that enable engineering and business users to leverage AI capabilities within their day‑to‑day workflows
• Architect, implement, and manage CI/CD pipelines to support rapid, reliable deployment of AI/ML models and related services
• Deploy and manage AI/ML workloads across one or more major cloud platforms (AWS, Azure, GCP, OCI), leveraging native AI/ML services as appropriate
• Implement MLOps best practices, including experiment tracking, model registry, feature stores, monitoring, and automated retraining where appropriate
• Optimize model performance and cost through techniques such as quantization, pruning, distillation, and efficient distributed training
• Integrate and operationalize LLM and NLP solutions (e.g., transformers, RAG systems) to support text understanding, summarization, Q&A, and other intelligent automation use cases
• Collaborate with data engineers, cloud engineers, and domain experts to design robust data pipelines and architectures for AI/ML workloads, including time‑series, image/video, and text data
• Ensure that all solutions adhere to security, compliance, and governance standards, especially when working with sensitive or regulated data
• Provide technical leadership, mentorship, and guidance to junior engineers and peers, promoting best practices in AI/ML engineering, DevOps, and software craftsmanship
• Produce high‑quality technical documentation, including architecture diagrams, API specifications, deployment runbooks, and user guides
• Participate in technical planning, backlog grooming, and estimation; contribute to roadmap development for AI/ML capabilities

Skills

• 8+ years of professional software engineering experience, with substantial work in AI/ML and cloud‑native development
• Experience with at least one major cloud platform (AWS, Azure, GCP, or OCI) for deploying and managing ML workloads
• Hands‑on experience with cloud AI/ML services such as Azure AI, AWS SageMaker/Bedrock, GCP Vertex AI, or OCI AI Services
• Strong DevOps background, including: Ansible for configuration management and automation, Docker for containerization, Kubernetes for container orchestration, CI/CD best practices for automated build, test, and deployment
• Proficiency with relational and non‑relational databases, including: SQL (PostgreSQL, MySQL), NoSQL and vector databases for similarity search and embedding‑based retrieval
• Strong scripting skills in both: Bash, PowerShell
• Proven experience designing and maintaining CI/CD pipelines using: Azure DevOps, GitHub Actions, Jenkins, or similar automation tools
• 3–5+ years of production‑level Python development (primary implementation language)
• 3+ years of experience with NLP and LLMs, including: Transformer models (BERT, GPT, T5, etc.), RAG (Retrieval‑Augmented Generation) systems, Fine‑tuning and prompt engineering, Building LLM‑based applications
• 3+ years of experience with time‑series data, including: Forecasting models, Anomaly detection, Sequential data modeling, Real‑time monitoring systems
• 3+ years of experience building recommender systems, such as: Collaborative filtering, Ranking models, Personalization engines, Content recommendation pipelines
• Production experience with MLOps tools and platforms, such as: MLflow, Weights & Biases, Kubeflow, Airflow, or similar systems for orchestration, tracking, and model lifecycle management
• Experience with distributed training, including: Large‑scale model training, Multi‑GPU and/or multi‑node setups, Data/model parallelism and performance optimization
• Production computer vision experience using: PyTorch and/or TensorFlow, OpenCV, YOLO or similar frameworks for object detection and segmentation, Real‑time inference and deployment workflows
• Experience with feature stores (e.g., Feast, Tecton) and/or advanced feature engineering techniques
• Hands‑on experience with model optimization techniques: Quantization, Pruning, Knowledge distillation
• Experience working with LLM ecosystems such as: Ollama, Hugging Face, Other non‑frontier / open‑weight models
• Demonstrated AI/ML production track record: Built and deployed at least 2–3+ ML models serving real users (beyond experimental or research‑only projects)
• Must be able to pass a background check. May require additional background checks as required by projects and/or clients at any time during employment
• Exceptional interpersonal skills with the ability to communicate in a clear, professional, and articulate manner
• Exceptional verbal and written communication skills
• Excellent organizational, analytical, and problem-solving skills with high-level attention to detail
• Proven ability to multitask and prioritize in a fast past environment with changing priorities; adaptable to change and a quick learner
• Must be self-motivated and able to work well independently as well as on a multi-functional team
• Ability to handle sensitive and confidential information appropriately
• Proficient in MS Office, Word, Outlook, PowerPoint, and Excel
• 1+ year of experience with Geospatial Information Systems (GIS) and analyzing or modeling spatial data
• Prior experience in one or more of the following domains: Transportation, Logistics, Smart city or urban infrastructure
• Background applying computer vision to infrastructure or vehicular data, including: Object detection, Image segmentation, Video or sensor data analysis
• Familiarity with public sector data compliance, security, and governance, such as: Data classification and handling, Access control and audit requirements, Regulatory and policy constraints for government data
• Experience with Unreal Engine in the context of: Real‑world digital twinning, Simulation or immersive visualization of physical environments
• Experience integrating or building solutions with: Google Maps APIs, Cesium or similar 3D mapping/geospatial visualization platforms
• Experience with Polygonflow Dash and its capabilities for: 3D workflows, Visualization pipelines, Automation of complex modeling or simulation tasks

Benefits

• Medical, Dental and Vision Insurance; Wellness Program
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Short-Term and Long-Term Disability options
• Basic Life and AD&D Insurance (Company Provided)
• Voluntary Life and AD&D options
• 401(k) Retirement Savings Plan with matching after one year
• Paid Time Off

Company Overview