Senior Software Engineer

Senior Software Engineer focusing on AI/ML engineering and data-intensive systems, building cloud-native SaaS platforms, AI-powered features, data pipelines, and scalable ML serving infrastructure on AWS, with a hybrid work model in Boston.

Responsibilities

• Design, develop, and deploy machine learning models and AI-powered features for production SaaS products.
• Maintain scalable data pipelines for ingestion, transformation, and enrichment of large, complex datasets.
• Build model-serving infrastructure using AWS SageMaker, Lambda, and container-based deployment patterns.
• Incorporate LLM integrations, RAG architectures, and generative AI capabilities 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.
• Promote best practices in design, code quality, and system design across the team.
• Contribute to all stages of the SDLC: requirements review, design, development, testing, and deployment.
• 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 focused on solving customer problems as a top priority.

Requirements

• B.S. in Computer Science, Mathematics, Statistics, or a related quantitative field; M.S. or Ph.D. preferred.
• 5+ years of software engineering experience, including 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.

Technologies

• Python
• C#/.NET
• AWS
• SageMaker
• S3
• Glue
• Athena
• Lambda
• EC2
• CloudWatch
• Docker
• Kubernetes
• scikit-learn
• PyTorch
• TensorFlow
• XGBoost
• Apache Spark
• Airflow
• dbt
• PostgreSQL
• MSSQL
• SQL
• REST API
• Angular
• React

Benefits

• Health Insurance
• Retirement Plan
• Disability benefits
• Paid Time Off

NICE TO HAVE

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