Senior DevOps Engineer

• 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

• 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

Benefits

• A fun, lively startup culture

• Ample opportunities to learn and take on new responsibilities in a fast-paced, growth-mode startup

• A culture of employee engagement, diversity and inclusion

• Core values-based leadership

• Open vacation policy - we all work hard and take time for ourselves when we need it

• Full benefits package including parental leave, a matching 401k program, and medical, dental, vision, disability, and life insurance

• Generous stock options - we all get to own a piece of what we’re building- You have strong infrastructure-as-code skills with Terraform and understand how to manage state, modules, and multi-environment configurations

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

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

• 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

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

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

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

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

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

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

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

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

• Experience in regulated industries (insurance, financial services, healthcare) is a strong plus

• Container orchestration (ECS, EKS)

• Monitoring and observability platforms (Datadog, CloudWatch)

• Data infrastructure (Redshift, or similar data warehousing; Airflow, dbt, Dagster or similar pipeline tools) is a strong plus

• A genuine curiosity about AI and emerging technologies, paired with the judgment to apply them thoughtfully and responsibly