About the Company

Solutions Engineer (AI, Identity & Data Security) Location: [India] Minimum Experience: 8+ years in Pre-Sales/ Solution Engineering or a similar senior technical customer-facing role

About the Role

The Sales Engineer is the technical authority and narrative driver in customer engagements. This role is responsible for translating complex AI, Identity, and Data Protection challenges into defensible, real-world solutions—while helping customers understand not just how something works, but why it matters. This role blends deep hands-on technical expertise with storytelling, big-picture ('paint the picture') thinking, and collaborative problem solving. You will work with prospects to obtain the technical win by designing a viable technical solution with an amazing product that can be applied to various scenarios. You will operate across AI security, LLMs, AI agents, MCP, DLP, and Identity, partnering closely with Sales, Product, and Engineering to close deals and influence product direction.

Responsibilities

Technical Discovery & Storytelling
Lead technical discovery for AI security, DLP, and Identity-driven use cases.
Translate complex security architectures into transparent narratives that resonate with:
CISOs and VP's
Security leaders
Architects
Engineers
Business stakeholders
'Paint the big picture' by connecting AI usage, identity trust, and data protection into a cohesive story.
Clearly articulate what problems are solvable today, what are partially solvable, and what are structural limitations.

Architecture & Solution Design
Design and present end-to-end architectures covering:
LLM and AI agent workflows (human + non-human identities)




Data protection, inspection, and policy enforcement
Identity, authentication, authorization, and trust boundaries
Build, configure, and run demos and POCs using Dockerized components.
Integrate enterprise environments including:
Microsoft Entra ID (Azure AD), Okta
Microsoft Intune, Jamf Pro
Explain and demonstrate AI pipelines using:
LangChain, LangGraph
MCP-style agent orchestration patterns
Lead deep dives into DLP architectures, including:
What DLP can realistically detect and enforce
Where traditional DLP breaks down (AI, agents, encrypted channels, context loss)
Common false assumptions customers have about DLP coverage
Help customers understand enforcement gaps, bypass scenarios, and risk trade-offs without overselling.

Workshops & Collaborative Problem Solving
Facilitate technical workshops and brainstorming sessions with customer teams.
Co-design architectures and controls with customers rather than prescribing static solutions.
Whiteboard flows covering:
AI access paths
Identity trust boundaries
Data movement and enforcement points
Use workshops to uncover real constraints and drive solution alignment.

Execution & Field Innovation
Troubleshoot complex issues across AI pipelines, identity flows, and data paths.




Create interim or custom solutions using Python, YAML, and cloud services when product features are missing.
Collaborate with Product and Engineering to validate feasibility and relay field feedback.
Maintain technical assets, demo configurations, and documentation in GitHub.

Qualifications

Deep, practical understanding of Data Loss Prevention (DLP):
Inspection, classification, enforcement points
Real-world limitations and bypass scenarios
Strong hands-on knowledge of:
AI systems, LLMs, AI agents
Emerging AI security risks and abuse patterns
Solid foundation in Identity & Access Management (IAM):
SSO, OAuth/OIDC, tokens, policy enforcement
Practical experience with:
Docker
Linux
Python
YAML-based configuration
Familiarity with endpoint and device trust tooling:
Microsoft Intune
Jamf Pro
Experience with cloud platforms (AWS, Azure, or GCP).
Comfortable using GitHub for code, configs, and version control.
Exceptional communication, storytelling, and executive-level presentation skills.
Ability to lead workshops, whiteboard complex systems, and drive collaborative design sessions.
Experience in an early startup environment preferred.

What Success Looks Like

Customers trust you not just as a technologist, but as a strategic advisor.
Complex AI, identity, and DLP concepts are understood clearly at every stakeholder level.
POCs reflect real customer constraints, not idealized lab conditions.
Workshops result in alignment, not confusion.
Deals move forward because solutions are credible, transparent, and defensible—even as the product evolves.

📌 Solutions Engineer (AI, Identity & Data Security) (Mumbai)
🏢 QuilrAI
📍 Mumbai