Senior Technical Consultant – AI Security

AHEAD

. Deploy, integrate, and operationalize AI security capabilities in customer and enterprise environments .

Posted 11/10/2026full-timeRemote • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in deploying and operationalizing AI security capabilities, integrating cloud-native architectures, and developing technical proposals for AI security engagements. Proficient in securing AI systems and implementing automation workflows while collaborating with cross-functional teams and stakeholders.

Highest-signal resume keywords

AI Security EngineeringCloud-Native Architecture DeploymentData Integration and Telemetry PipelinesTechnical Proposal DevelopmentScripting and Automation (Python, PowerShell, Bash)

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI SecurityCloud-Native ArchitectureData IntegrationTelemetry PipelinesSecurity AnalyticsPrompt Injection DefenseModel Risk ScoringAnomaly DetectionIntegration PatternsAutomation Workflows

Soft Skills

CollaborationMentoringCommunication

Tools & Technologies

AWSAzureGCPAPIsWebhooksEvent-Driven Workflows

Industry Keywords

AI GovernanceCompliance RequirementsModel EvaluationAdversarial TestingData Leakage Prevention

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Deploy, integrate, and operationalize AI security capabilities in customer and enterprise environments
Develop technical proposals, statements of work, and solution architectures for AI security engagements
Translate business, operational, and AI security requirements into deployable architectures and implementation plans
Partner with internal and external stakeholders to align solutions with AI governance, compliance requirements, and platform strategy
Design and implement integrations across AI platforms, model registries, LLM gateways, vector databases, and AI-enabled security tooling
Build and configure cloud-native data ingestion, normalization, and enrichment pipelines for AI telemetry, model activity logs, and prompt/response data
Integrate APIs, webhooks, message queues, and automation workflows across AI operations, identity, cloud, and application ecosystems
Develop reusable deployment patterns, templates, and technical assets
Operationalize security controls and guardrails for AI systems, including prompt injection defense, model access controls, data leakage prevention, and agentic workflow monitoring
Secure non-human identities, including service accounts, API keys, tokens, and autonomous agent credentials
Implement red teaming, adversarial testing, model risk scoring, and anomaly detection for AI systems
Implement secure and governed automation for AI security monitoring, investigation, and response
Support resiliency, observability, performance, and scale requirements
Troubleshoot integration issues, deployment blockers, and production challenges
Improve reliability and maintainability through documentation, testing, monitoring, and standardized engineering practices
Collaborate across AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, and product or customer teams
Communicate technical concepts to technical and non-technical stakeholders
Mentor engineers and consultants and contribute to AI security implementation and solution design best practices
Provide field feedback to influence platform roadmap, product direction, and architectural standards

Requirements

What you’ll need

7+ years of experience in security engineering, AI engineering, platform engineering, forward deployed engineering, solutions consulting, or related technical roles, with demonstrated progression to a principal or senior consulting level
Hands-on experience securing AI systems, LLM applications, or AI production pipelines
Experience deploying cloud-native architectures on at least one major cloud provider such as AWS, Azure, or GCP
Strong background in data integration, telemetry pipelines, normalization, and security analytics workflows applied to AI systems
Experience working directly with customers, executive stakeholders, or cross-functional delivery teams in implementation-focused environments
Proven experience developing technical proposals, statements of work, and scoping documents for customer engagements
Strong understanding of AI security risks, including prompt injection, model theft, data poisoning, adversarial attacks, and agentic AI risks, alongside foundational cloud, identity, and endpoint security
Experience with scripting and automation using tools such as Python, PowerShell, or Bash
Familiarity with APIs and integration patterns including REST, webhooks, and event-driven workflows
Working knowledge of LLMs, vector search, retrieval-augmented generation, model evaluation, and AI assistants or agents
Bachelor’s degree in computer science, Information Security, Engineering, or equivalent practical experience

Benefits

Comp & perks

Comprehensive health insurance coverage for employees, with options to extend coverage to dependents
Paid time off and company holidays, along with additional leave benefits as per policy
Flexible work arrangements, supporting work-life balance
Learning and development opportunities to support continuous growth and upskilling
Employee wellness initiatives and programs focused on physical and mental well-being
Retirement and statutory benefits in line with India regulations
Inclusive and people-first culture, with a strong focus on collaboration and ownership
Cross-department training and development
Sponsored certifications and credentials for continued learning
Access to top-notch technologies in a multi-million-dollar lab