IND Senior Software Engineer

The Hartford; Rangareddy; On-site; INR 11,407,000 - 15,209,000; Full time

Job summary

The Hartford seeks an experienced Senior Software Engineer for GCC123 to advance model monitoring, data quality, and observable ML pipelines. You will collaborate with data scientists to onboard models, implement drift and KPI monitoring, and support retraining strategies in a scalable cloud environment.

Responsibilities include building CI/CD pipelines, applying IaC practices, and delivering production-grade ML applications with strong reliability and security focus.

Qualifications

• Bachelor’s or Master’s in Computer Science, Engineering or closely related field with 5+ years of exp (or 3+ years with advanced degree).
• 3+ years collaborating with engineering/data science on ML systems focusing on reliability and security.
• 4+ years with public cloud platforms (GCP/AWS/Azure) to deploy ML workloads.
• 2+ years building IaC (Terraform) for ML environments and pipelines.
• 5+ years of software development using Python/Java incl. production-grade ML apps.
• 3+ years working with ML/AI frameworks (TensorFlow, scikit-learn, SageMaker, Vertex AI).
• 3+ years understanding model/data drift and related monitoring/validation strategies.
• 3+ years of CI/CD and MLOps practices in agile SAFe environments.

Responsibilities

• Collaborate with Data Scientists to onboard models into monitoring systems and maintain drift checks.
• Support retraining workflows when drift is detected.
• Implement monitoring frameworks for data drift, training-serving skew, and KPIs in production.
• Configure automated alerts for anomalies in input/output distributions and performance.
• Build and maintain CI/CD pipelines for monitoring solutions and model updates.

Skills

Python

Java

Agile/Safe

Communication

Problem solving

Education

Bachelor's or Master's in CS/Engineering

Tools

Terraform

CI/CD tooling

Arize

Job description

IND Senior Software Engineer - GCC123

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 Responsibilities

Model 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

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