Sr. DevOps Engineer II

Insurance touches people during some of the most challenging moments in their lives. Hi Marley is on a mission to transform how the P C industry communicates, making those moments faster, easier, and more empathetic for carriers and the customers they serve. We build AI-powered software that keeps everyone in the claims conversation informed and connected. If you believe insurance can combine operational excellence and automation with a human touch, we’d love to meet you.

We are looking for a Sr. DevOps Engineer II to help us build and scale the infrastructure that powers both our core platform and our rapidly growing agentic AI services. You will be at the intersection of cloud infrastructure, AI operations, and platform engineering — building the foundation that enables Hi Marley to   operate   reliably at enterprise scale while deploying autonomous AI agents in regulated insurance workflows.   You'll   also be expected to raise the bar for the teams around you — setting infrastructure standards, driving technical decisions in ambiguous situations, and helping less experienced engineers grow their operational instincts. Teamwork and shared enthusiasm are a core part of our culture, which is why this role involves joining us in the Boston office for 2-3 days each week.

What You’ll Do:

Design and   operate   cloud infrastructure on AWS that supports both our core SaaS platform and our agentic AI services, ensuring reliability, scalability, and cost efficiency

Build and   maintain   AI/ML infrastructure   and monitoring for LLM-powered agentic services

Establish and enforce infrastructure-as-code standards using Terraform, defining the patterns other engineers follow for environment parity, drift detection, and automated compliance validation

Implement observability beyond availability — data integrity monitoring, SLO frameworks with error budgets, and automated regression detection for both platform and AI services

Build deployment automation including pre-deployment verification, migration script validation, and codified rollback procedures to   eliminate   human-memory dependencies

Support big data infrastructure: data pipelines, warehousing (Redshift), and analytics tooling that enables reporting, BI, and AI training workflows

Implement security and compliance controls for AI workloads   operating   in regulated carrier environments — including audit logging, access governance, and configuration management

Drive environment parity across all infrastructure   with automated drift detection and remediation

Improve   disaster recovery capabilities: documented and rehearsed DR procedures, defined RTO/RPO by service tier, and tested recovery runbooks

Lead architecture reviews for new services, integrations, and AI agent deployments — partnering with engineering, product, and security to ensure infrastructure decisions are sound before they ship

Innovate on developer experience: reduce friction in testing environments, CI/CD pipelines, and local development workflows

Act as a technical anchor for infrastructure decisions across teams — providing clarity when requirements are ambiguous and helping the organization converge on consistent, scalable approaches

What We’re Looking For:

6- + years of DevOps/SRE/Platform Engineering experience

2+ years of experience building or operating AI/ML infrastructure (model serving, inference, LLM orchestration, or agentic systems)

Bachelor’s degree in Computer Science , Engineering, or equivalent experience

You have built and operated infrastructure for   traditional and   AI   or   ML workloads at a SaaS company

You naturally step up to lead technical conversations, and people across teams seek you out when infrastructure decisions get complicated

You have deep experience with AWS cloud services (ECS, Lambda, SageMaker, Bedrock, S3, DynamoDB, Redshift, or equivalent)

You have strong infrastructure-as-code skills with Terraform and understand how to manage state, modules, and multi-environment configurations

You understand data infrastructure: pipelines, warehousing, ETL/ELT, and how to support analytics at scale

You think about observability as more than dashboards — you care about data integrity, SLOs, error budgets, and catching silent failures

You have experience with compliance-sensitive environments and understand why audit trails, access governance, and change management matter

You are comfortable operating in a fast-moving environment where AI capabilities are evolving   rapidly   and infrastructure decisions have regulatory implications

You communicate well with both engineering and non-technical stakeholders

Track record   of leading cross-team technical initiatives and mentoring engineers on infrastructure and operational best practices

Strong   proficiency   in at least one programming language (Python, Go, TypeScript, or similar)

Experience with:

C ontainer orchestration (ECS, EKS…