interface.ai

Education Requirements:

• Bachelor's degree in Computer Science, Information Security, or a related field.

Experience Requirements:

• 6+ years of experience in security engineering with a primary focus on application and cloud security

• Proficiency with programming languages like Java, Python, JavaScript and SQL

• In-depth knowledge of application security vulnerabilities and threat modeling

• Deep familiarity with AWS security architecture and services

• Experience with DevSecOps tools (SAST, DAST, container scanning)

Other Requirements:

• Certifications such as OSCP, AWS Security Specialty, or CISSP preferred

• Experience in high-compliance industries (financial services, healthcare) preferred

Responsibilities:

• Perform security assessments across our application stack

• Build and maintain secure SDLC practices

• Design and maintain secure configurations for AWS environments

• Champion a shift-left approach to security

• Support compliance initiatives by building and documenting controls

Experience Requirements:

• 4+ years of experience in backend engineering

• Strong backend programming skills like Java, Node.JS, or similar

• Proven experience building and scaling distributed services, APIs, and event-driven systems

• Familiarity with infrastructure tools such as Docker, Kubernetes, and CI/CD pipelines

• Experience integrating services with data stores and message queues

Other Requirements:

• Experience working on AI-enabled or ML-integrated platforms preferred

• Prior experience working in fast-paced, high-growth product teams

Responsibilities:

• Design and build high-availability, low-latency services

• Contribute to orchestration logic for tool invocation and session management

• Integrate backend systems with AI components like language models

• Identify and resolve performance bottlenecks and scalability challenges

• Participate in design and architecture reviews and mentor junior engineers

Experience Requirements:

• 5–8 years of core DevOps experience building infrastructure from scratch

• Deep expertise in Docker, Kubernetes, Helm, and container orchestration

• Hands-on with Terraform, Crossplane, and declarative infrastructure management

• Proven ability to deploy AI/LLMs and agent workflows reliably in production

• Expertise with vector databases (tuning and scaling)

Other Requirements:

• Proficiency in monitoring and logging tools (Prometheus, Grafana)

• Proficiency in scripting/programming (Python, Bash, Go)

• Knowledge of security best practices in cloud environments

Responsibilities:

• Design, implement, and scale infrastructure across AWS, GCP, or Azure

• Build and manage Kubernetes clusters and service mesh

• Architect CI/CD pipelines (ArgoCD/GitOps, Jenkins)

• Define and track key metrics for AI/LLMs and agent workflows

• Implement end-to-end tracing for multi-turn queries using OpenTelemetry