Senior Security Engineer

About the role

Eleos Health builds a system of action for community-based care, using its Polaris AI to help behavioral health, hospice, home health and other care teams act proactively. As a Senior Security Engineer you will be a hands-on technical leader in the security organization, part builder and part architect, sitting in design reviews, pushing back constructively on architecture choices, prototyping missing controls and helping R&D ship faster and safer. The role suits someone who thinks in systems, codes when needed and is energized by securing modern AI-driven, multi-cloud environments.

Key responsibilities

• Act as security architect for new initiatives: join design and concept meetings with R&D before code is written, and produce threat models, reference designs and decision documents.
• Partner with R&D as a peer, translating security requirements into engineering language and engineering trade-offs into risk language for leadership.
• Own security across the multi-cloud footprint (AWS, GCP, Azure), designing controls for identity, network, workload and data protection.
• Drive AI security: defend against prompt injection, model abuse, training-data integrity, agentic-workflow risks, MCP/tool-use exposure, secrets in prompts and supply-chain risk in the AI stack.
• Lead data security: classification, encryption, key management, DLP, access governance and data-flow mapping.
• Evaluate and implement new technologies through POCs and end-to-end deployment, and evolve the security stack.
• Write code: automate controls, build internal tools, contribute to detection pipelines and integrate security into CI/CD.

Required profile

• 5+ years in security engineering, application security or cloud security, with meaningful hands-on time.
• Strong software development background, having shipped production code and read others' code fluently.
• Experience introducing and operationalizing new security technologies, not just maintaining them.
• Track record of close collaboration with engineering teams, including design and code reviews.
• Direct experience with AI/ML security, securing LLM applications, agentic systems, model deployments or AI infrastructure.

Required skills

• Multi-cloud security (IAM, networking, workload security, infrastructure-as-code)
• Data security at scale: classification, encryption, key management, access controls
• Architect-level thinking on trust boundaries, blast radius and failure modes