The Principal Technical Consultant (Forward Deployed Engineer) for AI Security is a senior, customer-facing technical leader responsible for deploying, integrating, and operationalizing AI security capabilities in real-world customer and enterprise environments, with a focus on securing AI systems, LLM applications, and agentic workflows. This role works at the intersection of engineering, AI, security, data, and customer success to translate complex requirements into scalable, production-ready solutions.
This individual partners closely with security leaders, AI engineers, data scientists, platform teams, and infrastructure stakeholders to implement AI security controls, secure AI development pipelines, integrate security tooling for AI systems, and accelerate time to value. The ideal candidate brings 10+ years of security experience and combines deep technical expertise in AI systems, model and data security, and cloud platforms with proven experience developing technical proposals and statements of work, leading cross-team collaboration, and driving customer-facing delivery at a principal level.
Responsibilities
Customer and Stakeholder Delivery
Serve as the senior technical lead for deploying and operationalizing AI security solutions in customer or enterprise environments
Develop technical proposals, statements of work, and solution architectures that scope AI security engagements and support business development efforts
Translate business, operational, and AI security requirements into deployable architectures and implementation plans
Partner with internal and external stakeholders to ensure solutions are aligned to AI governance, compliance requirements, and long-term platform strategy
Act as a trusted advisor and technical point of contact during onboarding, implementation, rollout, and optimization phases
Solution Implementation and Integration
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 supporting AI systems
Develop reusable deployment patterns, templates, and technical assets to accelerate future AI security implementations
AI Security Operations
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 (NHI), including service accounts, API keys, tokens, and autonomous agent credentials, across AI and agentic workflows
Work with AI, detection engineering, and data teams to implement red teaming, adversarial testing, model risk scoring, and anomaly detection for AI systems
Help define data requirements, feedback loops, and operational guardrails needed to secure AI systems in production environments
Ensure deployed solutions are practical, measurable, and aligned to AI governance and risk objectives
Automation and Reliability
Implement secure and governed automation for AI security monitoring, investigation, and response use cases across heterogeneous environments
Support resiliency, observability, performance, and scale requirements for deployed AI security solutions
Troubleshoot integration issues, deployment blockers, and production challenges in partnership with AI, platform, cloud, and security teams
Improve reliability and maintainability through documentation, testing, monitoring, and standardized engineering practices
Cross-Functional Teaming
Work cross-team collaboration across AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, and product or customer teams
Communicate technical concepts clearly to both technical and non-technical stakeholders, including executive audiences
Mentor and develop engineers and consultants, contributing to best practices for AI security implementation, delivery, and technical solution design
Provide field feedback to influence platform roadmap, product direction, and architectural standards
Support the practice in pre-sales activities, proposal development, and client presentations
Required Qualifications
10+ 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
Ability to lead technical engagements, drive execution, and influence outcomes without direct authority
Demonstrated ability to enable cross-team collaboration across engineering, security, data science, and business stakeholders
Technical Skills
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 AI concepts including LLMs, vector search, retrieval-augmented generation, model evaluation, and AI assistants or agents
Strong problem-solving skills, execution mindset, and ability to operate effectively in ambiguous, fast-moving environments
Preferred Qualifications
Experience with implementation and integration of OpenAI models, specifically Daybreak Blue and/or Red.
Experience with implementation and integration of Anthropic models.
Experience with AI red teaming, adversarial AI testing, or AI governance frameworks such as the NIST AI RMF, ISO/IEC 42001, or the OWASP Top 10 for LLM Applications
Familiarity with the MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) knowledge base for AI-specific attack techniques and mitigations
Experience deploying solutions in regulated or compliance-sensitive environments
Familiarity with infrastructure as code, CI/CD workflows, and AI production delivery practices
Experience building reusable implementation frameworks or field engineering playbooks
Relevant certifications are a plus, including cloud, security, or AI-specific certifications
Education
Bachelor’s degree in computer science, Information Security, Engineering, or equivalent practical experience
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
India Employment Benefits include:
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
