Job Description

This hybrid role is a member of a multidisciplinary Agile team responsible for developing, deploying, and stewarding mission-critical data systems, micro-services, web applications, and AI/ML solutions. The incumbent supports the full Application Lifecycle Management (analysis, design, development, validation, deployment, support) and collaborates with senior engineers and business stakeholders to deliver effective software and AI solutions. The role also involves supporting the development and deployment of machine learning models, primarily using AWS services.

Principle Responsibilities:

• Assistin designing, developing, and deploying machine learning models using AWS services (SageMaker, Lambda, EC2, S3, Redshift).

• Supportautomated workflows for model training and deployment (AWS Step Functions, Lambda).

• Monitor model performance and suggest adjustments.

• Work across the full ALM lifecycle on system elements (clients, servers, services, middleware, persistence, communication).

• Participate in design reviews, code reviews, and practice reviews.

• Ensure technical approaches align with architectural blueprints and approved practices.

• Manage and preprocess datasets using AWS data services.

• Engage in software configuration management, CI/CD, automated testing, andDevSecOpspractices.

• Collaborate with data scientists, software engineers, and business stakeholders to understand requirements and deliver solutions.

• Maintain documentation of models, processes, workflows, and technical approaches.

• Participate in Level 2+ support for team products and systems.

• Engage inongoing operational and practice improvements.

• Follow best practices for data privacy and protection, ensuring compliance with organizational security policies.

Knowledge, Skills, and Abilities:

• Effective communication and documentation skills.

• Strong analytical and problem-solving capabilities.

• Agile mindset and ability to adapt in a fast-paced environment.

• Ability to understand the big picture and focus on critical-path work.

• Experience in insurance, financial services, or other highly regulated industries is highly desirable.

Technical Skills:

• Bachelor’s degree in Computer Science, Data Science, IT, or related field (preferred).

• 1–3+yearsprofessional experience in AI/ML and enterprise-class SOA/micro-service systems and web-based applications.

• Experience with AWS services: SageMaker, Lambda, EC2, S3, EFS, SNS, SQS,EventBridge, Kinesis, Aurora, DynamoDB, RDS Proxy, Glue, Athena, Redshift/Spectrum.

• Familiarity with Azure “Cloud Native” solutions concepts is a plus.

• Basicproficiencyin Python and machine learning libraries (TensorFlow,PyTorch, scikit-learn).

• Proficiencywith C# and at least one of: Python, PowerShell, SQL, JavaScript.

• Understanding ofOOA/OOD, system modeling (UML preferred), and distributed systems patterns (SOA/micro-services, CQRS, event-stream processing, pub/sub messaging).

• Experience with containerization (Docker), version control (Git/GitHub), CI/CD tooling (Jenkins, Bamboo, TeamCity, AWSCodePipeline).

• Experience with automated BDD test tooling (SpecFlow, Cucumber).

• Familiarity with messaging serialization (Protobufs, Thrift, Avro, JSON), RDMS persistence (ODBC/SQL), NoSQL repositories, MoM platforms (MQ, JMS, Kafka), JavaScript browser UI frameworks (Angular, React).

• Experience with code profiling, optimization, andanalysistooling is a plus.

• Familiarity with Kanban, Lean, or XP practices is a plus.

Preferred Qualifications:

• AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect (Associate level).

• Experience with NLP, computer vision, reinforcement learning, and generative models.

Venerable Values:

• We Are Courageous – We think critically, ask “why?” and seek out creative solutions.

• We Are Curious – We take calculated risks, learn from our failures, and challenge traditional ways of thinking.

• We Are Connected – Weare connected to each other, ourcustomersand our community.

Please note:The use of AI tools (such as ChatGPT or similar platforms) during interviews is not permitted without the prior approval of Venerable, as the use of such tools may interfere with company confidentiality, misrepresent a candidate’s skills and experience or otherwise conflict with Venerable’s hiring policies. If you are selected for an interview and a reasonable accommodation is needed, please notify the Venerable Human Resources recruiter aligned to the open position in which you are interviewing for.

If Venerable, in its sole discretion, determines that AI is being used during an interview without prior approval, Venerable reserves the right to end the interview early and/or disqualify a candidate.

#LI-AB1

Venerable Values:

Every position at Venerable has responsibility for living out the company's values as described here:

We are Courageous - We think critically, ask "why?" and seek out creative solutions.

We are Curious - We take calculated risks, learn from out failures, and challenge traditional ways of thinking.

We are Connected - We are connected to each other, our customers and our community.

Please note: The use of AI tools (such as ChatGPT or similar platforms) during interviews is not permitted without the prior approval of Venerable, as the use of such tools may interfere with company confidentiality, misrepresent a candidate’s skills and experience or otherwise conflict with Venerable’s hiring policies. If you are selected for an interview and a reasonable accommodation is needed, please notify the Venerable Human Resources recruiter aligned to the open position in which you are interviewing for.

If Venerable, in its sole discretion, determines that AI is being used during an interview without prior approval, Venerable reserves the right to end the interview early and/or disqualify a candidate.