We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
Key ResponsibilitiesModel Monitoring & Observability
- Collaborate with Data Scientists to onboard models into monitoring systems (e.g., MHM database) and maintain configuration files for drift and performance checks.
- Support retraining workflows when drift or degradation is detected.
- Implement monitoring frameworks to track data drift, training-serving skew, and model performance metrics in production environments.
- Utilize observability tools like Arize to set up monitors for accuracy, precision, recall, and other KPIs.
- Configure automated alerts for anomalies in input/output distributions and performance degradation.
Data Quality Assurance
- Perform QC checks on incoming data to validate integrity and completeness before model scoring.
- Develop pipelines for continuous validation of data sources and ensure compliance with quality standards.
Performance Evaluation
- Monitor KPIs such as accuracy, precision, recall, and fairness across demographic slices.
- Conduct root-cause analysis for performance degradation and recommend retraining strategies.
Infrastructure & Automation
- Build and maintain CI/CD pipelines for deploying monitoring solutions and model updates.
- Leverage cloud technologies for scalable monitoring and orchestration.
Documentation & Reporting
- Maintain detailed logs of monitoring activities, thresholds, and alerts.
- Provide periodic reports on model health, including drift metrics and performance trends.
Required Skills & Experience:
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a closely related field; 5+ years of professional experience with a Bachelor’s degree, or 3+ years of experience accepted with an advanced engineering degree combined with applied academic, internship, or hands‑on project experience focused on machine learning, GenAI, or full‑stack software development.
• 3+ years of experience collaborating with engineering leads and data science teams on the design, development, and scaling of machine learning systems, with a focus on reliability, scalability, and security.
• 4+ years of hands‑on experience working with public cloud platforms such as Google Cloud Platform, AWS, and/or Azure to deploy, operate, and scale ML workloads.
• 2+ years of hands‑on experience building Infrastructure as Code (IaC) using tools such as Terraform to support ML environments and pipelines.
• 5+ years of software development experience using programming languages such as Python, Java, or equivalent object‑oriented or scripting languages, including production‑grade ML or data applications.
• 3+ years of experience working with machine learning and AI frameworks or platforms such as TensorFlow, scikit‑learn, Anaconda, SageMaker, Vertex AI, or Agentic AI tooling.
• 3+ years of experience understanding model drift and data drift concepts and contributing to the design and implementation of monitoring, validation, and retraining strategies for ML and AI systems.
• 3+ years of working knowledge of CI/CD and MLOps practices, including automated testing, model validation, automated deployments, and integration pipelines.
• 3+ years of experience working in agile development environments, with SAFe experience required.
• 4+ years of experience collaborating and partnering with business leaders, engineering teams, and data science stakeholders to deliver machine learning solutions aligned to business outcomes.
• Excellent written and verbal communication skills, with the ability to explain technical concepts clearly to diverse audiences.
• Familiarity with agentic productivity and AI developer tools such as Claude Code, Gemini CLI, OpenAI Codex, or similar tools is a plus.
• Experience enabling or supporting enterprise AI services such as Gemini Enterprise, Amazon Q, Microsoft Copilot, or similar platforms is a plus.
• Strong analytical, critical thinking, and problem‑solving abilities, with a demonstrated willingness to challenge the status quo, take ownership, and drive innovation and continuous improvement in AI platform development.
• Ability to work both independently and collaboratively in a fast‑paced, agile environment, demonstrating accountability, initiative, and a bias for action.
Nice to Have
- Understanding of Agile framework is a plus
- Experience leveraging Gen AI tools to accelerate insight generation
About Us | Our Culture | What It’s Like to Work Here
Skills Required
- Bachelor's or master's degree in Computer Science, Engineering, or a closely related field
- 5+ years of professional experience with a bachelor's degree, or 3+ years with an advanced engineering degree plus relevant applied academic, internship, or hands-on project experience
- 3+ years collaborating with engineering leads and data science teams on machine learning system design, development, and scaling
- 4+ years of hands-on experience with public cloud platforms such as Google Cloud Platform, AWS, and/or Azure
- 2+ years building Infrastructure as Code using tools such as Terraform
- 5+ years of software development experience using Python, Java, or equivalent object-oriented or scripting languages
- 3+ years working with machine learning and AI frameworks or platforms such as TensorFlow, scikit-learn, Anaconda, SageMaker, Vertex AI, or Agentic AI tooling
- 3+ years understanding model drift and data drift and contributing to monitoring, validation, and retraining strategies
- 3+ years of CI/CD and MLOps experience, including automated testing, model validation, deployments, and integration pipelines
- 3+ years working in agile development environments, with SAFe experience
- 4+ years collaborating with business leaders, engineering teams, and data science stakeholders to deliver machine learning solutions
- Excellent written and verbal communication skills
- Strong analytical, critical thinking, and problem-solving abilities
- Ability to work independently and collaboratively in a fast-paced agile environment
- Familiarity with Claude Code, Gemini CLI, OpenAI Codex, or similar AI developer tools
- Experience supporting enterprise AI services such as Gemini Enterprise, Amazon Q, Microsoft Copilot, or similar platforms
- Understanding of Agile framework
- Experience using generative AI tools to accelerate insight generation
The Hartford Financial Services Group, Inc. Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Hartford Financial Services Group, Inc. and has not been reviewed or approved by The Hartford Financial Services Group, Inc..
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Retirement Support — A 401(k) with matching plus an additional company contribution, alongside an employee stock purchase plan and no‑cost financial planning, signals robust long‑term savings support. HSAs/FSAs and related financial tools further strengthen overall financial well‑being.
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Leave & Time Off Breadth — At least 25 days of PTO to start, options to buy or roll over time, and paid parental leave indicate broad time‑off support. Paid leave for organ and bone marrow donation and generous disability coverage extend protection for significant life events.
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Healthcare Strength — Multiple medical, dental, and vision options with the company covering most medical and dental premiums reflect strong core health coverage. Wellness programs, fitness reimbursements, well‑being credits, and accessible behavioral health services expand depth and accessibility.
The Hartford Financial Services Group, Inc. Insights
What We Do
Human achievement is at the heart of what we do. We put our belief into action by not only ensuring individuals and businesses are well protected, but by going even further – making an impact in ways that go beyond an insurance policy






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