IND Senior Software Engineer

The Hartford India; Hyderabad; Vor Ort; INR 2.500.000 - 4.000.000; Vollzeit

Zusammenfassung

The Hartford India is seeking an experienced Senior Software Engineer to lead ML monitoring, data quality, and observability initiatives. You will collaborate with data scientists and engineers to deploy scalable ML systems in the cloud, build CI/CD pipelines, and ensure reliability, security, and governance across production workloads.

You will work in a fast-paced, agile environment, employing best practices in ML Ops, model drift detection, retraining strategies, and performance evaluation to

Qualifikationen

• 5+ years of professional experience in ML/AI or full-stack software development.
• Experience with public cloud platforms and building ML pipelines.
• Hands-on with IaC and CI/CD for ML environments.

Aufgaben

• Onboard models into monitoring systems and maintain drift/performance checks.
• Support retraining workflows when drift is detected.
• Implement monitoring frameworks for data drift, training-serving skew, and KPIs.
• Use observability tools like Arize to monitor accuracy, precision, recall, and reliability.
• Configure automated alerts for anomalies in input/output distributions.
• Perform QC checks on data and build pipelines for continuous validation.
• Monitor KPIs and perform root-cause analysis for degradation.
• Build and maintain CI/CD pipelines; leverage cloud for scalable monitoring.
• Document monitoring activity, thresholds, and reports.

Kenntnisse

Python/Java

CI/CD / MLOps

ML systems design

Agile / SAFe

Cloud platforms (GCP/AWS/Azure)

Ausbildung

Bachelor’s or Master’s in CS/Engineering

Tools

Terraform

TensorFlow

scikit-learn

SageMaker

Vertex AI

Arize

Jobbeschreibung

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