Mudals Technologies

Role Overview

We are looking for an AI Security Engineer with a strong foundation in both Artificial Intelligence and Cyber Security. This role focuses on building secure AI systems,

protecting LLM-based applications, and embedding security across the entire AI lifecycle, from data to deployment.

Key Highlights

• Work hands-on with LLMs and Generative AI use cases with a strong security focus
• Design and secure RAG-based intelligent applications
• Implement secure vector databases and semantic search systems
• Drive AI security across MLOps and DevSecOps pipelines
• Opportunity to build and scale secure AI solutions in production environments

Required Skills & Qualifications:

• 5+ years of experience in Python development
• Strong experience with frameworks like Django, Flask, or FastAPI
• Hands-on expertise in AWS cloud services (EC2, Lambda, S3, RDS, ECS, etc.)
• Experience with Hugging Face, LangChain, Transformers
• Strong understanding of microservices and distributed systems
• Experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB), vector databases
• Proficiency with version control practices
• Experience with CI/CD pipelines and automation tools

Must-Have Skills(AI- specific)

• Strong proficiency in Python
• Hands-on experience with ML, DL & Large Language Models (LLMs),
• Experience with RAG architecture and secure data pipelines
• Strong background in Cyber Security / Information Security domain
• Understanding of application security, cloud security, and network security fundamentals

Security-Specific Expertise

Strong knowledge of:

• OWASP Top 10 / API Security Top 10, Encryption (data at rest & in transit)
• Secure coding practices, Vulnerability Assessment & Penetration Testing (VAPT)
• Authentication & Authorization (OAuth2, JWT, SSO)
• Prompt Injection Attacks, Identity & Access Management (IAM)
• Data Leakage & Sensitive Data Exposure
• Model Poisoning / Adversarial Attacks
• Threat Modeling (STRIDE / MITRE ATT&CK)
• Secrets management (Vault, KMS, etc.)

Responsibilities

• Design and implement secure AI/ML architectures
• Perform AI security assessments, threat modeling, and VAPT
• Build and enforce LLM guardrails and security controls
• Collaborate with engineering teams to embed security-by-design principles
• Monitor and respond to AI-specific and cyber security threats
• Ensure compliance, governance, and risk management for AI systems

Job Summary:

We are seeking a DevOps Engineer (AWS) with deep expertise in Terraform, Atlantis, and large-scale multi-cloud environments (200–300+ accounts/subscriptions). This is a client-facing consulting role, responsible for designing and governing secure, scalable infrastructure and CI/CD platforms across enterprise environments.

This role goes beyond implementation, you will define standards, governance models, and automation frameworks for large organizations operating at scale.

Key Responsibilities:

Cloud Platforms / AWS Expertise

• AWS (Expert) – Organizations, IAM, VPC, Security services
• Strong hands-on experience with AWS Service Catalog to design, publish, and manage standardized, secure infrastructure products across multi-account AWS environments
• Proven ability to enforce governance, compliance, and cost controls by integrating Service Catalog with IAM, SCPs, and CI/CD pipelines
• Experience with Azure or GCP (multi-cloud exposure required) Enterprise DevSecOps Architecture
• Architect and standardize end-to-end DevSecOps platforms
• Design secure, scalable CI/CD pipelines using Jenkins & GitHub Actions
• Embed security gates (SAST, DAST, SCA, container security) into pipelines
• Define reusable pipeline templates across multiple teams/business units Terraform + Atlantis (Must-Have, Core Focus)
• Design and manage large-scale Terraform architecture across 200–300+ cloud accounts
• Implement Terraform modules, remote backends, and state isolation strategies
• Build and manage Atlantis workflows for automated Terraform plan/apply
• Enforce:Code reviews & approvals for infra changes Policy-as-code (OPA / Sentinel)
• Drift detection & remediation

Multi-Cloud Architecture (AWS + Azure/GCP)

• Architect multi-cloud landing zones and governance frameworks
• Manage large account structures:
• AWS Organizations (multi-account strategy) Azure Management Groups / Subscriptions
• Implement:Network segmentation (VPC/VNet design) Identity federation (SSO, IAM, RBAC) Cross-account access models
• Ensure high availability, scalability, and cost optimization Security & Compliance at Scale
• Implement DevSecOps controls aligned with SOC 2, PCI-DSS, GDPR
• Integrate tools like: JFrog Xray (SCA) SonarQube (SAST) Trivy / Prisma / Wiz (container & cloud security)
• Build policy-as-code frameworks for compliance enforcement
• Automate evidence collection for audits

Artifact & Dependency Management

• Architect secure artifact lifecycle using JFrog Artifactory
• Implement access control, immutability, and vulnerability scanning
• Standardize dependency management across teams Observability & Reliability
• Implement centralized logging/monitoring:
• CloudWatch, ELK, Prometheus/Grafana
• Define SLOs/SLIs for platform reliability
• Reduce MTTR via automation and alerting

Consulting & Leadership

• Act as a trusted advisor to enterprise clients
• Lead architecture discussions and DevSecOps transformation programs
• Mentor teams and enforce engineering best practices
• Drive platform adoption across multiple business units

Required Skills:

Infrastructure as Code (Core)

• Terraform (Expert level)
• Atlantis (Hands-on implementation at scale)
• Strong experience with multi-account architecture (200–300+ accounts)

DevOps Tooling

• Jenkins (advanced pipelines)
• GitHub Actions (enterprise workflows)
• GitOps practices

Cloud Platforms

• AWS (Expert) – Organizations, IAM, VPC, Security services
• Experience with Azure or GCP (multi-cloud exposure required)

Security Stack

• SAST, DAST, SCA tools integration
• Container security & Kubernetes security
• Secrets management (Vault / AWS Secrets Manager)

Programming/Scripting

• Python / Bash (automation focus)

Preferred Qualifications:

• Experience with Kubernetes (EKS/AKS/GKE) at scale
• Knowledge of Zero Trust Architecture
• Experience with OPA / Sentinel (policy-as-code)
• Familiarity with platform engineering concepts (Internal Developer Platforms)

Certifications (Good to Have)

• AWS Solutions Architect – Professional
• Terraform Associate / Advanced Terraform certifications
• CISSP / CKS (Kubernetes Security)

What Makes This Role Premium

• Ownership of large-scale (200–300 account) cloud environments
• Direct impact on enterprise DevSecOps maturity
• Client-facing architecture & strategy role (not just execution)
• Opportunity to define organization-wide standards