Staff Software Engineer/AI-ML

IND Staff Engineer - GCC094

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.

Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.

Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.

Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.

Accountable for design, development and maintenance of Models as Service

Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.

Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams

Delivery of critical milestones for model deployment in the AWS and GCP clouds.

Adopt and promote MLOps best practices to the Data Science community.

Minimum Requirements

Development experience using both the AWS and GCP suite of tools.

Familiarity with SageMaker, Streamlit, web security, credentials and API management tools

Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.

Experience building and deploying webservices in a cloud environment.

Experience building CICD pipeline using Jenkins or equivalent

Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar

Expert-level Github experience, including Github Actions

Strong object oriented development experience using Python, Java, C#

Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.) and RDBMS platforms such as Redshift, Snowflake or BigQuery

Experience in end to end model development lifecycle, from ideation through post production monitoring.

Experience with workflow automation platforms (Apache Airflow, Autosys, similar)

Experience with Solution Design and Architecture of data pipelines

Basic understanding of Data Science model development life cycle

Preferred Skills

Fundamentally strong with Data Structures and algorithms.

Experience working with Docker, Kubernetes and EC2 environment.

Experience building ML and data pipeline and orchestration services

Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn,

Experience working in an Agile framework.

ML engineering, data manipulation and application development

Python development experience

Working with IAC, developing CICD pipelines

Experience in the insurance or broader financial services industry

SQL development experience

Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes

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