Job description

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 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)   M onitoring and observability platforms (Datadog, CloudWatch)   D ata infrastructure (Redshift, or similar data warehousing; Airflow,   dbt ,   Dagster   or 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 Compensation, Benefits & Perks: At Hi Marley, we are committed to fair and transparent pay practices. The annual base salary for this role is expected to fall within the range of [$119,000–$221,000], depending on experience, skills, qualifications, and location. Offers are determined based on these factors as well as internal peer equity. It’s most common for new hires to start near the midpoint of the range, allowing room for growth as employees develop in their role. In addition to base pay, we offer a comprehensive total rewards package that supports both your wellbeing and professional growth, including: Equity grants for all employees A 4% matching 401(k) program Medical, dental, vision, disability, and life insurance coverage for employees working 30+ hours per week Monthly wellness stipend Paid parental leave A flexible vacation policy - we all work hard and take time when we need it Who We Are: At Hi Marley, our culture is built on three core values that every employee embodies: Max Courage – We encourage our team, our customers, and their customers to dream big, try new ideas, and maximize impact by measuring risk. Be Humble – We lead with appreciation and promote a culture of humility, compassion, and openness to learn from anyone, anywhere. Ubuntu (“I am because we are”) – We believe true success is much bigger than any single individual or company. By aligning our individual aims behind a shared purpose, we can achieve our fullest potential — together. Life at Hi Marley: Life at Hi Marley is shaped by collaboration, learning, and genuine connection. We’re proud to foster an environment where people can do their best work, feel supported, and grow alongside a team that celebrates both individuality and shared purpose. A fun, lively startup culture that embraces creativity and innovation Core values-based leadership that guides our decision-making and daily interactions A culture of engagement, diversity, inclusion, and belonging — everyone’s voice matters Flexible, hybrid work environment that values balance and trust Ample opportunities to learn, take on new challenges, and make an impact in a fast-growing organization Meaningful work that directly supports our mission to help people and organizations communicate with empathy and clarity Hi Marley is proud to be an equal employment opportunity employer. We celebrate diversity and do not discriminate based on gender, sexual orientation, gender identity, religion, race, veteran status, disability status, or any other characteristic protected by applicable law. We are committed to building an inclusive work environment representing a variety of backgrounds, perspectives, and skills, where all employees are encouraged to be their authentic selves. Hi Marley participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. For more information, please review the documents under "E-Verify Poster" here: e-verify.uscis.gov

Requirements

Must-haves

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
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

Nice-to-haves

None flagged.

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Keywords to mirror

aiawsmlllmci/cdpythongotypescript

Platform: greenhouse
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Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Parental Leave

Wellness