Senior Software Engineer

hackajob is collaborating with Verisk to connect them with exceptional professionals for this role.

Description

We 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.

Responsibilities

AI & Data Engineering

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• Design, build, and deploy machine learning models and AI-powered features into production SaaS products
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• Maintain scalable data pipelines for ingestion, transformation, and enrichment of large, complex datasets
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• Develop model-serving infrastructure using AWS SageMaker, Lambda, and container-based deployment patterns
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• Apply LLM integrations, RAG architectures, and generative AI capabilities where appropriate to enhance product functionality
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• Own data quality, observability, and monitoring for AI/ML workloads in production
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Software Engineering & Architecture

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• Lead the design and implementation of cloud-native microservices and APIs (Python, C#/.NET) on AWS
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• Drive best practices in design, code quality, and system design across the team
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• Contribute to all stages of the SDLC: requirements review, design, development, testing, and deployment
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• Conduct code reviews and mentor team members on engineering standards
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• Proactively identify technical risks and communicate them early to course-correct
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• Participate in roadmap planning, scoping, and technology feasibility assessments
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• Contribute to a culture where solving customer problems is always the highest priority
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Qualifications

Required

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

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• Experience with LLMs, prompt engineering, or RAG (Retrieval-Augmented Generation) systems
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• Familiarity with MLflow, Weights & Biases, or other ML lifecycle management tools
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• AWS Certification (Machine Learning Specialty, Solutions Architect, or equivalent)
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• Experience with geospatial data, catastrophe modeling, or climate/weather datasets
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• Full-stack experience with Angular or React and .NET Core
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• Background in the insurance, reinsurance, or financial services industries
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#LI-LM03
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