Principal Software Engineer
Liberty Mutual
Principal Software Engineer
- ID
- 2026-74788
- Position Type
- Full-Time
- Job Grade
- 18
- Department
- 0055-13750 GDS - ECPM
- Market
- Corporate Center
- Minimum Salary
- USD $120,000.00/Yr.
- Maximum Salary
- USD $225,000.00/Yr.
- Recruiter
- Damon Oliver
- Internal Application Deadline
- 3/17/2026
Description
Hiring Manager: Steven Guyardi
We deliver our customers peace of mind every day by helping them protect what they value most. Our passion for placing the customer at the center of everything we do is driving a transformational shift at Liberty Mutual. Operating as a tech startup within a Fortune 100 company, we are leading a digital disruption that will redefine how people experience insurance.
At Liberty, you'll thrive in a hybrid setting that fosters in-person collaboration, innovation and growth. This approach optimizes both remote and in-person interactions, enabling you to connect and ideate with your team and deepen valuable relationships across the company, while still enjoying the flexibility of remote work for focused tasks and projects.
This role has a hybrid work schedule (2 days onsite) and we are considering candidates based in Portsmouth, NH, Boston, MA, Plano, TX.
Job Introduction:
The Enterprise Core Platform Modernization (ECPM) team within the Global Digital Services (GDS) organization is looking to hire a dynamic Principal Software Engineer. The candidate will drive key technical initiatives to strengthen and scale our enterprise modernization platform and automation factory. In this role, you’ll translate architectural direction into repeatable, scalable engineering patterns; define validation, observability, security, and resiliency standards for modernization outputs; and support teams and vendors through complex, cross‑system integrations. You’ll help shape and enable both replatforming and retirement modernization initiatives, ensuring repeatable approaches for transforming, migrating, or decommissioning legacy systems. This position blends hands-on technical leadership, tool and platform assessment, and mentoring to elevate engineering practices across the modernization program, including the adoption of AI‑assisted engineering workflows and structured prompting methods.
About the job:
- Lead complex, cross-platform technical initiatives and act as a primary escalation for high-severity, cross-system issues.
- Translate architectural direction into implementable patterns, standards, and platform components that scale across the modernization factory.
- Define reusable patterns, automation frameworks, and validation mechanisms that ensure consistent, accurate, and high-quality modernization outputs.
- Identify systemic technical risks and drive mitigation plans.
- Partner with architects, platform teams, vendors, and program leadership to ensure technical alignment and smooth execution.
- Guide engineering teams on implementation tradeoffs, scalability, and technical best practices.
- Mentor engineers and elevate engineering capability across teams.
- Contribute to implementation of AI-assisted engineering workflows and structured prompt practices.
- Establish guardrails, evaluation metrics, and observability for AI-driven outputs used in modernization.
- Evaluate tools and platforms, run targeted POCs, and recommend enterprise adoption plans.
Qualifications
- Bachelor’s degree in a technical or business discipline, or equivalent experience.
- Minimum 8+ years Software Engineering experience.
- Fluency in Java, Python, Node.js, or similar languages used in ML and full-stack development.
- Familiarity with Apache Kafka, Springboot, Kubernetes, AWS services and best practices, including Lambda, S3, SageMaker, ECS/EKS, Bedrock etc.
- Proven track record leading complex technical initiatives across multiple systems, platforms, or integration layers.
- Familiarity with cloud platforms (AWS/Azure/GCP) and enterprise platform considerations (security, identity, scalability).
- Experience with MLOps and model deployment practices (e.g., containerization, GPU inference, vector databases).
- Hands-on experience with AI-assisted engineering tools or prompt engineering techniques.
- Strong hands-on technical depth with advanced debugging and problem-solving ability.
- Deep understanding of distributed systems, integrations, and automation frameworks.
- Proven ability to influence technical direction without formal authority.
- Experience working across teams to standardize engineering approaches and practices.
- Ability to operate effectively in technically complex and ambiguous environments.
- Experience evaluating engineering tools or platforms for enterprise adoption.
Employees may apply for a new role after completing 12 months of employment in their current position.
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