Sr. Security Engineer II
Secure the company's internal AI environment—LLM integrations, agents, MCP connectors, and data pipelines—through threat modeling, adversarial testing, and compliance evidence, using Python and AWS in a hybrid Boston setting.
- Compensation
- $121K–$226K / yr
- Location
- Hybrid - Boston, MA
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Security
- Posted
Skills
Must have
- 5+ years in security engineering, application security, or infrastructure security with hands-on exposure to AI/ML systems
- Experience securing or building LLM-based systems, agentic frameworks, or ML pipelines in cloud environments
- Understanding of AI-specific attack surfaces: prompt injection, tool-use exploitation, privilege escalation, data poisoning, model/training-data leakage
- Hands-on familiarity building with AI systems
- Strong proficiency in Python and experience building security tooling, automation, and testing
- Strong working knowledge of AWS security: IAM, networking, container isolation, encryption, and monitoring
- Familiarity with compliance frameworks (SOC 2, ISO 27001, ISO 42001, NIST AI RMF) and mapping controls to audit requirements
- Ability to communicate technical risk clearly to engineers, auditors, and stakeholders
Nice to have
- Experience running or contributing to AI red-teaming or adversarial testing
- Experience with MCPs, agent orchestration frameworks, or similar agentic infrastructure
- Background in DLP, monitoring, or observability for AI or cloud workloads
- Experience at a growth-stage B2B SaaS company
Full description
Insurance plays an important role in people’s lives, providing protection and peace of mind through life’s adventures and unexpected turns. In the moments that matter, people want to know their insurer is there for them. At Hi Marley, we help insurers deliver on that promise through communication that brings greater clarity and connection to the policyholder experience.
About the role
Our teams are building LLM integrations, agents, and MCP connectors into the tools they use every day, and you'll make sure they do it securely. You'll work side by side with the people building those tools, shaping the security architecture of our corporate and cloud environment and writing the guardrails that let teams move quickly without reinventing controls. You don't need to be an AI security specialist. If you think in systems, write real code, and want to learn the AI attack surface by doing, you'll love this role.
What you'll do
- Shape the security architecture of our corporate and cloud environment, from identity and SaaS configuration to the AWS accounts behind our business and AI tools
- Build guardrails as code with Terraform and policy tooling, and lead threat modeling and design reviews before new tools go live
- Secure our agentic workloads with isolation, scoped credentials, and data boundaries, and help test them against risks like prompt injection
- Design controls that produce audit evidence by default for our SOC 2 Type II and ISO 42001 programs
What you'll bring
- 5+ years in security engineering, cloud security, or infrastructure security, including leading threat modeling and design reviews
- Hands-on experience securing AWS and corporate identity, plus strong Python and security controls built as code with Terraform or similar
- A track record running vulnerability management and producing audit evidence for SOC 2, ISO 27001, or a similar framework, and explaining risk clearly to engineers and auditors alike
- Real interest in how AI changes the attack surface, and able to work from our Boston office 3 days a week
Nice to have
- Experience securing LLM-based systems, agent frameworks, or MCP connectors
- Familiarity with ISO/IEC 42001 or the NIST AI RMF
- Detection engineering or SIEM experience in cloud and SaaS environments
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 [$121,000-$200,000], 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.