{"id":4032056,"url":"https://alion.io/job/ahead-principal-technical-consultant-ai-security","title":"Principal Technical Consultant - AI Security","company":{"id":3614,"name":"AHEAD","domain":"ahead.com","url":"https://alion.io/company/ahead","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":73,"open_postings":37,"ghost_share":0,"stale_share":0.865,"repost_share":0.027,"time_to_fill_p50_days":74,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Solutions","role_family":"Solutions","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PowerShell","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Red Teaming","optional":false},{"name":"Rest API","optional":false},{"name":"Anthropic","optional":true},{"name":"CI/CD","optional":true},{"name":"NIST AI RMF","optional":true},{"name":"OpenAI","optional":true},{"name":"OWASP Top 10","optional":true}],"status":"live","first_seen_at":"2026-11-10T15:41:39Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-10T18:55:40Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"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.\nThis 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.\nResponsibilities\nCustomer and Stakeholder Delivery\nServe as the senior technical lead for deploying and operationalizing AI security solutions in customer or enterprise environments\nDevelop technical proposals, statements of work, and solution architectures that scope AI security engagements and support business development efforts\nTranslate business, operational, and AI security requirements into deployable architectures and implementation plans\nPartner with internal and external stakeholders to ensure solutions are aligned to AI governance, compliance requirements, and long-term platform strategy\nAct as a trusted advisor and technical point of contact during onboarding, implementation, rollout, and optimization phases\nSolution Implementation and Integration\nDesign and implement integrations across AI platforms, model registries, LLM gateways, vector databases, and AI-enabled security tooling\nBuild and configure cloud-native data ingestion, normalization, and enrichment pipelines for AI telemetry, model activity logs, and prompt/response data\nIntegrate APIs, webhooks, message queues, and automation workflows across AI operations, identity, cloud, and application ecosystems supporting AI systems\nDevelop reusable deployment patterns, templates, and technical assets to accelerate future AI security implementations\nAI Security Operations\nOperationalize security controls and guardrails for AI systems, including prompt injection defense, model access controls, data leakage prevention, and agentic workflow monitoring\nSecure non-human identities (NHI), including service accounts, API keys, tokens, and autonomous agent credentials, across AI and agentic workflows\nWork with AI, detection engineering, and data teams to implement red teaming, adversarial testing, model risk scoring, and anomaly detection for AI systems\nHelp define data requirements, feedback loops, and operational guardrails needed to secure AI systems in production environments\nEnsure deployed solutions are practical, measurable, and aligned to AI governance and risk objectives\nAutomation and Reliability\nImplement secure and governed automation for AI security monitoring, investigation, and response use cases across heterogeneous environments\nSupport resiliency, observability, performance, and scale requirements for deployed AI security solutions\nTroubleshoot integration issues, deployment blockers, and production challenges in partnership with AI, platform, cloud, and security teams\nImprove reliability and maintainability through documentation, testing, monitoring, and standardized engineering practices\nCross-Functional Teaming\nWork cross-team collaboration across AI Engineering, Security Engineering, Data Science, Infrastructure, Sales, and product or customer teams\nCommunicate technical concepts clearly to both technical and non-technical stakeholders, including executive audiences\nMentor and develop engineers and consultants, contributing to best practices for AI security implementation, delivery, and technical solution design\nProvide field feedback to influence platform roadmap, product direction, and architectural standards\nSupport the practice in pre-sales activities, proposal development, and client presentations\nRequired Qualifications\n10+ 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\nHands-on experience securing AI systems, LLM applications, or AI production pipelines\nExperience deploying cloud-native architectures on at least one major cloud provider such as AWS, Azure, or GCP\nStrong background in data integration, telemetry pipelines, normalization, and security analytics workflows applied to AI systems\nExperience working directly with customers, executive stakeholders, or cross-functional delivery teams in implementation-focused environments\nProven experience developing technical proposals, statements of work, and scoping documents for customer engagements\nAbility to lead technical engagements, drive execution, and influence outcomes without direct authority\nDemonstrated ability to enable cross-team collaboration across engineering, security, data science, and business stakeholders\nTechnical Skills\nStrong 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\nExperience with scripting and automation using tools such as Python, PowerShell, or Bash\nFamiliarity with APIs and integration patterns including REST, webhooks, and event-driven workflows\nWorking knowledge of AI concepts including LLMs, vector search, retrieval-augmented generation, model evaluation, and AI assistants or agents\nStrong problem-solving skills, execution mindset, and ability to operate effectively in ambiguous, fast-moving environments\nPreferred Qualifications\nExperience with implementation and integration of OpenAI models, specifically Daybreak Blue and/or Red.\nExperience with implementation and integration of Anthropic models.\nExperience 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\nFamiliarity with the MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) knowledge base for AI-specific attack techniques and mitigations\nExperience deploying solutions in regulated or compliance-sensitive environments\nFamiliarity with infrastructure as code, CI/CD workflows, and AI production delivery practices\nExperience building reusable implementation frameworks or field engineering playbooks\nRelevant certifications are a plus, including cloud, security, or AI-specific certifications\nEducation\nBachelor’s degree in computer science, Information Security, Engineering, or equivalent practical experience","description_format":"text","description_chars":7110,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","IT Consulting & Digital Transformation","Managed IT Services (MSP)","AI Consulting & 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