Senior Software Engineer

Senior Software EngineerWe are hiring a Senior Software Engineer with deep expertise in AI/ML engineering and data-intensive systems to join our Catastrophic and Risk Solutions team. You will be a key technical contributor on a cross-functional Agile team building cloud-native SaaS platforms that sit at the intersection of cutting-edge science and production software. This role goes beyond traditional full-stack development — you will design and ship AI-powered features, build data pipelines, and architect scalable ML-serving infrastructure on AWS. This role is office-based in our Boston location, which has a flexible hybrid work model.ResponsibilitiesAI & Data EngineeringDesign, build, and deploy machine learning models and AI-powered features into production SaaS productsMaintain scalable data pipelines for ingestion, transformation, and enrichment of large, complex datasetsDevelop model-serving infrastructure using AWS SageMaker, Lambda, and container-based deployment patternsApply LLM integrations, RAG architectures, and generative AI capabilities where appropriate to enhance product functionalityOwn data quality, observability, and monitoring for AI/ML workloads in productionSoftware Engineering & ArchitectureLead the design and implementation of cloud-native microservices and APIs (Python, C#/.NET) on AWSDrive best practices in design, code quality, and system design across the teamContribute to all stages of the SDLC: requirements review, design, development, testing, and deploymentConduct code reviews and mentor team members on engineering standardsProactively identify technical risks and communicate them early to course-correctParticipate in roadmap planning, scoping, and technology feasibility assessmentsContribute to a culture where solving customer problems is always the highest priorityQualificationsRequiredB.S. in Computer Science, Mathematics, Statistics, or a related quantitative field; M.S. or Ph.D. preferred5+ years of software engineering experience, with at least 2 years in a senior or lead role on cloud-native AWS productsStrong Python skills for data engineering, ML pipelines, and API developmentHands-on experience with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoostExperience building and deploying production ML systems — model training, evaluation, versioning, and servingProficiency with AWS data and AI services: SageMaker, S3, Glue, Athena, Lambda, EC2, CloudWatchExperience with data pipeline tooling: Apache Spark, Airflow, dbt, or equivalentSolid 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 designFamiliarity with REST API design, microservices, and containerization (Docker, Kubernetes)Experience with Agile development methodologiesNice to HaveExperience with LLMs, prompt engineering, or RAG (Retrieval-Augmented Generation) systemsFamiliarity with MLflow, Weights & Biases, or other ML lifecycle management toolsAWS Certification (Machine Learning Specialty, Solutions Architect, or equivalent)Experience with geospatial data, catastrophe modeling, or climate/weather datasetsFull-stack experience with Angular or React and.NET CoreBackground in the insurance, reinsurance, or financial services industries