Member of Technical Staff, Security Engineering

Member of Technical Staff, Security Engineering at Inception Labs scores 15 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

San Mateo, United Statesleadfull_time

AI in this role

chatgptopenaiclaudedatabricks

ai-safety

Inception creates the world’s fastest, most efficient AI models. Our Mercury model is the world’s fastest reasoning LLM and first commercially available diffusion LLM, delivering 5x greater speed and efficiency than today’s LLMs, with best-in-class quality.
We are the AI researchers and engineers behind such breakthrough AI technologies as diffusion models, flash attention, and DPO.
The Role
We are hiring across seniority levels for a Founding Security Engineer to build the security foundation for a frontier AI platform serving enterprise customers — owning product/API security, enterprise security architecture, compliance readiness, and incident response as the company scales.
For a senior/staff-level role, we are looking for someone with 6+ years of experience who has operated as a TL/TLM or staff+ engineer, remains deeply hands-on, and can provide the leadership presence to make delegation and prioritization decisions as Inception grows. You'll be the first/early security leader at a company where security directly affects customer trust, revenue, and product velocity.
You'll own and drive the systems, processes, and infrastructure that make Inception secure by default: cloud security, network isolation, access controls, incident response, compliance readiness, secure engineering workflows, and customer-facing security requirements. This role is ideal for someone who lives and breathes security, but is still a builder at heart — someone who can design secure systems, write production code, automate workflows, and partner deeply with engineering teams.
This is not a narrow GRC, IT, AI safety, or policy-only role, and it is not AI-specific security research. We're looking for traditional enterprise/product security execution from an "inverted T" engineer: broad software engineering ability with a deep spike in security. You'll be the internal expert who helps us navigate enterprise security, privacy, compliance, and infrastructure risk as we scale — a technical leader, not a friction point for the engineering team.
What You'll Own

Software engineering fundamentals: This is a software engineering role with a security specialization. Expect to spend 70%+ of your time writing code, building security tools, and automating security best practices. You'll need strong command of CS fundamentals, to design, build, and maintain secure software systems.
Enterprise security architecture & threat modeling. Design secure systems and guide backend, product, and platform engineers on security architecture and threat modeling for Inception's customer-facing API and enterprise deployments.
API / product security. Lead proactive threat protection for a public API product handling enterprise usage, analogous to companies exposing API surfaces like ChatGPT or Claude.
Compliance, certifications, and enterprise readiness. Lead or materially drive security compliance and certifications, including SOC 2 (including ongoing Type 2 readiness) and ISO 27001, plus data privacy and security best practices.
VPC, GDPR, incident response, and 24/7 security coverage. Operate as a staff-level "all-in-one specialist" across VPC design, network isolation, GDPR, incident response, security monitoring, and operational visibility for production systems.
Secure infrastructure and tooling. Build and maintain secure infrastructure, automation, and internal tools across Inception's product, platform, and enterprise systems — improving developer velocity while raising the security baseline.
Engineering practices. Establish and promote secure development, code review, release management, vulnerability management, and incident response practices.
Pragmatic partnership. Review systems and architectures for security risks and help engineers make pragmatic tradeoffs. Contribute beyond a narrow security lane when needed, especially across backend, infrastructure, platform, and developer tooling.

You Might Be a Fit If

You have 6+ years of security engineering experience or equivalent staff-level depth, and have operated as a TL/TLM or staff+ engineer who still ships.
You've built security for enterprise-facing products, APIs, infrastructure, or compliance-heavy environments, and have worked with customers who have procurement, compliance, or customer-trust requirements.
You have hands-on experience with product/API security for customer-facing APIs.
You have driven or owned SOC 2, ISO 27001, GDPR, or comparable compliance and certification programs.
You've built or owned internal security systems, privacy infrastructure, identity and access management, encryption, cloud security controls, mTLS, policy systems, or security services exposed via APIs.
You're proficient in Python; comfort with at least one systems language such as Go, Rust, or C++ is a plus.
You're fluent with modern software development, CI/CD, deployment automation, Kubernetes/Docker, infrastructure as code, and cloud platforms such as AWS or Azure.
You can operate independently in a fast-moving startup without a large security organization around you, and bring startup pace rather than big-tech-only conservatism.
You partner with fast-moving engineering teams as an enabler, not a blocker, with strong empathy for customer experience and developer velocity.
BS/MS/PhD in Computer Science or a related field, or equivalent experience.

Nice to Have

Experience as an early or founding security engineer at a startup or fast-growing engineering organization, helping scale towards 100+ org size.
Experience preparing companies for enterprise customers, security reviews, SOC 2 Type 2, ISO 27001, GDPR, or similar programs.
Background in backend engineering, platform engineering, infrastructure, or DevOps before specializing in security.
Experience building security tooling, developer platforms, or automation that engineers actually use.
Familiarity with monitoring, observability, vulnerability management, and incident response tooling.
Experience securing AI/ML infrastructure, GPU-intensive workloads, inference pipelines, serving APIs, or large-scale cloud environments. (Direct AI-specific security experience is not required.)
Experience with application security, threat modeling, secure SDLC, privacy engineering, or customer-facing security reviews.

Compensation

The annual base salary range for this role is $200,000 – $350,000 USD. Final compensation is determined based on experience, skills, and qualifications. Equity and benefits are included in the total package.
Why Join Inception

Work with World-Class Talent: Collaborate with the inventors of diffusion models and leading AI researchers
Shape Foundational Technology: Your decisions will influence how the next generation of AI products are built and used
Immediate Impact: Join at the ground floor where your contributions directly shape product direction and company trajectory

Perks & Benefits

Competitive salary and equity in a rapidly growing startup
Flexible vacation and paid time off (PTO)
Health, dental, and vision insurance
401k match
Catered meals (breakfast, lunch, & dinner)
Commuter subsidies
A collaborative and inclusive culture

About UsInception creates the world’s fastest, most efficient AI models. Today’s autoregressive LLMs generate tokens sequentially, which makes them painfully slow and expensive. Inception’s diffusion-based LLMs (dLLMs) generate answers in parallel. They are 5x faster and more efficient, while delivering best-in-class quality.
Inception was co-founded by Stanford professor Stefano Ermon, who co-invented such breakthrough AI technologies as diffusion models, flash attention, and DPO, UCLA professor Aditya Grover, who co-invented node2vec, decision transformers, and d1 reasoning, and Cornell professor and Afresh co-founder Volodymyr Kuleshov, who co-invented MDLM and Block Diffusion.
We pioneered the application of diffusion to language, with world’s first (and only) commercially available dLLM, Mercury. We are currently deploying our large-scale diffusion LLMs at Fortune 500 companies. Diffusion is the technology behind today’s image and video AI, and we’re making it the standard for LLMs as well.
Our team includes engineers from AWS, Google DeepMind, Meta AI, Microsoft, HashiCorp, and OpenAI. Based in Palo Alto, CA, we are backed by top-tier venture capitalists, including Menlo Ventures, Mayfield, M12 (Microsoft’s venture fund), Snowflake Ventures, Databricks, and Innovation Endeavors, and by tech luminaries such as Andrew Ng, Andrej Karpathy, and Eric Schmidt.
If you are talented, innovative, and ambitious, come help us invent the future of AI.We are an equal opportunity employer and encourage candidates of all backgrounds to apply.

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Skills and AI tools this role asks for

AI SafetyChatGPTOpenAIClaudeDatabricks

Questions you could be asked

How do you think about the risk of an AI system in this kind of role failing silently?
Walk me through how you've used ChatGPT in your day-to-day work.
What are the limits of OpenAI that you've run into, and how did you work around them?
What's a project where you used Claude hands-on?
Walk me through how you've used Databricks in your day-to-day work.

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