Senior Software Engineer; DevOps

Requirements

• 6-+ years of Dev Ops/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 fortraditional andAIorML 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, Sage Maker, 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 evolvingrapidly and infrastructure decisions have regulatory implications
• You communicate well with both engineering and non-technical stakeholders
• Track recordof leading cross-team technical initiatives and mentoring engineers on infrastructure and operational best practices
• Strongproficiencyin at least one programming language (Python, Go, Type Script, or similar)
• Experience with:
• Container orchestration (ECS, EKS)
• Monitoring and observability platforms (Datadog, Cloud Watch)
• Data infrastructure (Redshift, or similar data warehousing; Airflow,dbt,Dagsteror similar pipeline tools) is a strong plus
• Experience in regulated industries (insurance, financial services, healthcare) is a strong plus
• A genuine curiosity about AI and emerging technologies, paired with the judgment to apply them thoughtfully and responsibly

• We are looking for a Sr. Dev Ops 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