Senior Software Engineer

Responsibilities

• Design, build, and deploy machine learning models and AI-powered features into production SaaS products
• Maintain scalable data pipelines for ingestion, transformation, and enrichment of large, complex datasets
• Develop model-serving infrastructure using AWS SageMaker, Lambda, and container-based deployment patterns
• Apply LLM integrations, RAG architectures, and generative AI capabilities where appropriate to enhance product functionality
• Own data quality, observability, and monitoring for AI/ML workloads in production
• Lead the design and implementation of cloud-native microservices and APIs (Python, C#/.NET) on AWS
• Drive best practices in design, code quality, and system design across the team
• Conduct code reviews and mentor team members on engineering standards
• Proactively identify technical risks and communicate them early to course-correct
• Participate in roadmap planning, scoping, and technology feasibility assessments
• Contribute to a culture where solving customer problems is always the highest priority

Qualifications

• B.S. in Computer Science, Mathematics, Statistics, or a related quantitative field; M.S. or Ph.D. preferred
• 5+ years of software engineering experience, with at least 2 years in a senior or lead role on cloud-native AWS products
• Strong Python skills for data engineering, ML pipelines, and API development
• Hands-on experience with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost
• Experience building and deploying production ML systems — model training, evaluation, versioning, and serving
• Proficiency with AWS data and AI services: SageMaker, S3, Glue, Athena, Lambda, EC2, CloudWatch
• Experience with data pipeline tooling: Apache Spark, Airflow, dbt, or equivalent
• Solid understanding of data modeling, SQL, and working with large-scale databases (PostgreSQL, MSSQL, or similar)
• Strong grasp of software engineering fundamentals: CI/CD, DevOps, testing, and system design
• Familiarity with REST API design, microservices, and containerization (Docker, Kubernetes)
• Experience with Agile development methodologies

Required Qualifications

• Experience with LLMs, prompt engineering, or RAG (Retrieval-Augmented Generation) systems is nice to have
• Familiarity with MLflow, Weights & Biases, or other ML lifecycle management tools is nice to have
• AWS Certification (Machine Learning Specialty, Solutions Architect, or equivalent) is nice to have
• Experience with geospatial data, catastrophe modeling, or climate/weather datasets is nice to have
• Full-stack experience with Angular or React and .NET Core is nice to have

About Us

We are a leading data analytics and technology partner to the global insurance industry. We empower communities and businesses to make better decisions on risk, faster. At Verisk, you'll have the chance to use your voice and build a rewarding career that's as unique as you are, with work flexibility and the support, coaching, and training you need to succeed.