---
title: 'Member of Technical Staff, Security Engineering at Inception'
canonical: 'https://feeny.ai/job/member-of-technical-staff-security-engineering-inception-bay-area-bkgnvmqqqyg1'
type: 'job'
last_seen: '2026-09-05'
---

# Member of Technical Staff, Security Engineering at Inception

- **Company:** Inception
- **Location:** Bay Area
- **Compensation:** $200k–$350k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-22
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.gem.com/inception/am9icG9zdDrOT4cf3ftZEDrqAbPzyFm5

## Job description

## The Role

We're hiring a hands-on Staff 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.

This is a senior/staff-level role 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.

## About Inception

## Company Overview
- **One-liner**: Inception is an AI research and product company building diffusion-based language models (dLLMs) for production applications, offering 5x faster inference than traditional autoregressive LLMs.
- **Entity Type**: Private (Seed-stage; $57M total funding)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: Not publicly available (earliest funding round dated March 2025)
- **Founders**: Stefano Ermon (CEO), Aditya Grover (Co-Founder & CTO), Volodymyr Kuleshov (Co-Founder)

## Core Business
- **Primary industry**: Artificial intelligence research and infrastructure; large language models (LLMs)
- **Target customers**: B2B developers, enterprises, and AI application builders requiring low-latency, high-volume LLM inference for multi-step agents and real-time products.
- **Mission or purpose**: “We’re building the next generation of LLMs” – enabling intelligent, responsive, and scalable AI applications through diffusion-based architectures.

## Products & Services
- **Mercury (dLLM family)**: The world’s first commercially available family of diffusion large language models. Generates output via a coarse-to-fine iterative refinement process over a small number of steps, achieving 5x greater speed than autoregressive models while maintaining best-in-class quality. Seamlessly integrates into existing LLM workflows.
- **Research technologies**: d1 Reasoning, Discrete Diffusion Guidance, Direct Preference Optimization, Flash Attention, Decision Transformers, and Diffusion Models – foundational contributions that underpin the company’s product.

## Market Standing
- **Valuation / Market Cap**: Not disclosed
- **Key Metric**: Total funding of $57M across two seed rounds (2025)
- **Notable Investors / Partners**: Menlo Ventures (led the $50M seed round), Amazon Web Services (non‑equity assistance), Eric Schmidt (individual investor)
- **Growth Signals**: Headcount grew 187.5% year‑over‑year to 39 employees; LinkedIn followers increased 240% yearly to ~11,800; active job postings across AI systems, engineering, research, product, and marketing; talent sourced from Google DeepMind, Stanford SAIL, Meta, Amazon, and Pixxel.

## Competitive Advantages
- **Diffusion paradigm**: Non‑autoregressive generation that allows parallel refinement and revision during inference, breaking the sequential token‑by‑token bottleneck of conventional LLMs.
- **Speed‑cost curve**: Delivers 5x faster output with a fundamentally different cost structure, critical for real‑time, multi‑step agent workflows.
- **Founding team pedigree**: Co‑founders have pioneered breakthroughs in model architectures (Flash Attention, Direct Preference Optimization) and have deep experience turning research into production systems at scale.

## Strategic Focus
- Scaling Mercury adoption by integrating dLLMs into existing LLM pipelines and targeting high‑volume, latency‑sensitive applications.
- Advancing research in diffusion‑based reasoning, reinforcement learning for language models, and training/serving infrastructure.
- Expanding the team across AI systems (kernels, inference, training infra), product engineering, and research to accelerate product‑market fit.

## Why Work Here
- **Culture**: A tight‑knit team of scientists, engineers, and builders focused on shipping frontier AI research. Emphasis on innovation, speed, and real‑world impact.
- **Work policy**: In‑office for most roles (Palo Alto HQ); a Marketing Intern position is listed as remote. Typical time on‑site is full‑time in the office.
- **Notable perks / engineering culture**: Opportunity to work on cutting‑edge diffusion LLMs from scratch, contribute to foundational research (papers published), and collaborate with alumni from top AI labs. Roles span from kernel engineering to RL infrastructure and product management.
- **Growth**: Rapidly scaling headcount (+187% YoY) with open positions across multiple disciplines, offering strong career progression in a high‑visibility startup.

## Sources
1. [inceptionlabs.ai/about](https://www.inceptionlabs.ai/about)
2. [inceptionlabs.ai/careers](https://www.inceptionlabs.ai/careers)
3. [jobs.gem.com/inception](https://jobs.gem.com/inception)
4. [linkedin.com/company/inception-labs-ai](https://linkedin.com/company/inception-labs-ai)
5. [builtin.com/company/inception](https://builtin.com/company/inception)

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