Hiring an AI security engineer in India

What the role owns

An AI security engineer owns the security of AI systems from design review to incident response.

How it differs from adjacent roles

The AI security engineer is accountable for adversarial behaviour. Adjacent roles test whether the system works, or secure software in general.

In banks the seat usually reports into the security function under the CISO; our FinTech CISO guide covers that line.

The evidence bar

Credible proof is an attack that worked on a real system, the control that stopped it, and the test that keeps it stopped. Ask for one complete story and probe each step.

On the CV, look for:

• A named system secured: a retrieval assistant over internal documents, a chatbot with account access, a coding, email or browser agent.
• Indirect prompt injection findings, where instructions hidden in a document, web page or email redirected the system.
• Agent permission work: scoped tool tokens, approval steps, separate read and write tools, secured MCP servers.
• Red-team coverage mapped to OWASP or MITRE ATLAS categories.
• Production guardrails with measured false positive rates and latency cost.
• Classic security depth: web application testing, cloud IAM, secrets management.

In the interview, strong candidates can explain:

• Why prompt injection has no complete fix, and which layered controls limit the blast radius: privilege separation, untrusted model output, approval gates, egress limits.
• How an exfiltration chain works, for example an injected instruction that makes an agent embed private data in an image URL.
• Why retrieval access control must be enforced at query time, not in the prompt.
• Why guardrail classifiers are a layer, not a perimeter, and how encoding, other languages or multi-turn setups bypass them.
• Model supply chain risk, including serialisation formats that execute code on load.

Red flags

• Equates AI security with jailbreaking a chatbot.
• Proposes "a better system prompt" as the main defence against injection.
• Has never looked at agent permissions, tool scopes or connector authentication.
• Lists guardrail products but cannot say what they miss.
• No grounding in application or cloud security.
• Findings with no fixes, or fixes with no regression tests.

Stack and tools

Tool lists change quickly; judgement about layered controls does not.

Two references anchor most interviews and audits. The OWASP Top 10 for LLM Applications 2026, published on 3 August 2026, replaced the 2025 edition; per OWASP and Help Net Security (6 August 2026), prompt injection stays first, sensitive information disclosure second and excessive agency rises to third, while system prompt leakage was broadened into hidden context exposure. OWASP also announced an Agent Control Standard for runtime enforcement in its September 2026 release. MITRE ATLAS is a living knowledge base of adversary tactics and techniques against AI systems, modelled on MITRE ATT&CK, which lets security operations teams map AI threats into language they already use.

Interview loop that works

Test attack and defence on a realistic agent, then test whether the candidate can make engineers ship the fix. Four stages are enough.

A practical exercise. Provide a sandboxed email agent that can read an inbox, search a knowledge base holding a seeded secret, and send email. Ask the candidate to exfiltrate the secret through an injection planted in an incoming email, document the chain, propose controls and write two regression tests. Strong candidates find the chain quickly and spend most of their time on permissions and approval design, not cleverer prompts.

Where they come from in India

The pool is small and mostly converted from application security, so source by attack and defence work done. Bengaluru leads, followed by Hyderabad, Pune, Delhi NCR and Chennai; Mumbai matters for banks.

• AI-native startups. Engineers who secured their own agents under customer security reviews.
• Product and SaaS companies. Product security teams that took on LLM features.
• Global capability centres. AI red teams and security architecture groups at bank and technology GCCs.
• IT services and security consultancies. Penetration testing and AI assurance practices; screen for depth beyond scanners.
• Research labs, BFSI and trading firms. Adversarial ML researchers, and security engineers used to audits and tight data controls.

Our AI jobs in India guide maps the wider market.

What they cost

AI security engineers price slightly above general security engineers, reflecting scarcity of people strong in both fields. The ranges below are SYTalent Market Data on 2027 annual fixed pay, Bengaluru reference market, from our software engineering and AI salaries benchmark.

Fixed pay excludes bonus and equity, and the benchmark flags this as one of the titles with the thinnest evidence. Big Tech, GCCs and FinTech tend to pay at or above these bands.

Hiring in GCCs, banks and regulated firms

In regulated entities, AI security is moving from best practice to audited control. Candidates need to produce evidence an auditor accepts, not only fixes.

• CERT-In. CERT-In issued Artificial Intelligence Security Auditing Guidelines, version 1.0, on 4 November 2026, according to a Cloud Security Alliance research note (6 November 2026). They cover AI systems operated in India or serving Indian users, including retrieval-augmented and multi-agent systems, use a four-tier risk model, and call for red-team exercises at the highest tier. CERT-In's 2022 six-hour incident reporting directions also apply to qualifying AI incidents.
• RBI. The RBI's draft model risk management guidance of 24 June 2026 covers AI and third-party models at regulated entities; summaries of the draft describe expected protections against prompt injection and adversarial inputs. The governance and model risk lead is the closest partner here.
• DPDP Act. Under the Digital Personal Data Protection Rules, notified on 14 November 2025, failing to maintain reasonable security safeguards can attract penalties of up to ₹250 crore, and AI leakage of personal data falls inside this.
• Data residency. Many banks and GCCs restrict which hosted models and regions may process production data, which shapes guardrail and logging design.

Our guide to AI jobs in fintech and banking covers the wider hiring picture.

How SYTalent runs these searches

SYTalent is a talent search firm across HFT, FinTech and AI, with 65+ clients and a 50K+ talent network. Our AI, deep tech and quantum practice maps AI security candidates by findings fixed and controls shipped; see an adjacent agentic AI engineers search, brief us or browse Roles.

Sources

Help Net Security (6 August 2026) and the Cloud Security Alliance (6 November 2026) are credited in plain text. Pay ranges are SYTalent Market Data.