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Were looking for an experienced, multidisciplinary Security Engineer with a strong technical foundation and the ability to learn and own new technologies and domains from the ground up.Youll join Corporate Security Engineering within our Cyber Defense organization, Youll design, implement, and mature the security controls that protect our business applications, workforce, and corporate environment.
Youll work closely with Cyber Defense, IT, DRE, R&D, People, Legal, and GRC to embed security controls at scale. Our strategy is AI-first and built on identity-centric controls, Zero Trust principles, and scalable automation.
Youll Own
The security posture of our corporate technology stack, including AI security, identity, DLP and insider risk, EDR, MDM, browser security, SSPM/CASB, network security, and email and collaboration security.
Zero Trust access policies for workforce and external users, along with hardening for macOS, Windows, and Linux endpoints, browsers, SaaS applications, and corporate networks.
Identity and access capabilities, including SSO, phishing-resistant MFA, passwordless authentication, conditional access, device trust, PAM, joiner-mover-leaver controls, and service-account hygiene.
The evaluation and rollout of new security technologies, taking solutions from proof of concept through production.
Automated workflows and API integrations that scale security controls without adding operational overhead or headcount.
SaaS, third-party, and AI governance, including SaaS configuration reviews, vendor security assessments, access reviews, OAuth governance, posture remediation, and enablement-first guardrails for employee AI tools.
Domain expertise for SecOps incident response and partnership with IT and R&D to embed security standards and operating procedures into day-to-day processes.
Youll Solve
How to protect a fast-growing SaaS companys corporate environment across a broad and evolving technology stack.
How to translate security risks into clear requirements, practical controls, and reliable production operations.
How to strengthen identity, endpoint, SaaS, network, email, and collaboration security through a unified Zero Trust approach.
How to automate security processes and integrate systems so controls remain effective as we scale.
How to enable employees to use SaaS and AI tools safely through thoughtful guardrails rather than blanket restrictions.
How to make security standards easy for partner teams to adopt by embedding them into operational workflows and SOPs.
Youll Impact
The security and resilience of our business applications, workforce, and corporate environment.
Our ability to scale securely through stronger identity-centric controls, Zero Trust access, endpoint hardening, and SaaS governance.

Required Senior Backend Engineer - AI Framework (Python)
As a Senior Backend Engineer on our AI Framework team, you will build the foundational platform that enables the entire organization to design, evaluate, deploy, and operate AI agents at scale. This is a new, high-impact team responsible for creating the frameworks, tools, and guardrails that power our agentic ecosystem.
Youll work deeply in the agentic space, designing systems for orchestration, evaluation, observability, and safety. The platforms you build will be used by multiple teams across, making your impact immediate and company-wide.
Youll Own:
Agentic Framework Architecture: Designing and building our internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our broader backend ecosystem.
Agent Runtime and Execution Engine: Building the runtime responsible for orchestrating agent execution, managing tool calls, maintaining state and memory, and ensuring reliable execution across distributed systems.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

We are looking for a Head of Forward Deployed Engineering to lead the team that turns our platform into live production systems inside the largest enterprises. You will own a team of 10+ FDEs (and growing), the delivery bar they are held to, and the outcomes they ship.
This is a player-coach role. You set the standard, build the system that enforces it, and stay close enough to the work to review a flow design and call out what's wrong.
What You'll Do
Own delivery outcomes. On-time go-lives, production stability and client satisfaction all land on your desk. You manage by data: delivery metrics, quality signals, escalation rates and client feedback.
Raise the bar. Run a clear performance system with a defined FDE bar, 30-60-90 ramps for new hires, and honest evaluations. Coach the people who can grow. Make the hard calls on those who can't.
Run the operating rhythm. Own the flow review forum, the deployment status cadence, and the on-site schedule across clients.
Grow the team. Own the hiring pipe, from sourcing through a practical interview loop to onboarding that gets new FDEs to independent delivery in 90 days.
Stay in the field. Show up at key clients, especially around go-lives. Your credibility comes from being in the room, not above it.

Were looking for a Senior Customer Solutions Architect to own strategic post-sales relationships and help customers build and mature their AI Security and Governance programs.

This role combines the technical and consultative strengths of a Solutions Engineer with long-term ownership of customer strategy, adoption, and value realization. Youll work with stakeholders ranging from security practitioners to CISOs, continuously discovering new use cases and translating customer priorities into phased plans with clear owners, timelines, and measurable outcomes.

Youll own the overall customer relationship and technical direction, including deployment roadmaps, success plans, quarterly business reviews, and platform expansion after the initial rollout. Sales will own commercial discussions and negotiations.

Youll partner with Customer Engineers on deployment, integrations, configuration, and troubleshooting, while bringing enough technical depth to scope solutions, investigate issues, and challenge assumptions with specific findings.

What Youll Do
Strategic Customer Leadership: Own post-sales relationships for a focused portfolio of enterprise customers, building trusted partnerships across technical practitioners, security leaders, and executives.
Customer Planning & Execution: Build and drive deployment roadmaps and success plans with clear phases, owners, and target dates. Lead quarterly business reviews to assess progress, demonstrate value, and align on next steps.
Discovery & AI Security Advisory: Understand each customers AI environment, security program, priorities, and risks. Work with CISOs, AI governance stakeholders, and architecture teams to translate those priorities into practical implementation plans.
Technical Scoping & Escalations: Scope deployments, review architecture and integration requirements, and use API documentation and logs to investigate issues. Validate assumptions and engage R&D with specific technical findings, clear questions, and well-defined escalation requests.
Value, Adoption & Platform Expansion: Connect customer objectives to Nomas capabilities, define measurable outcomes, and drive adoption beyond the initial rollout. Identify additional workloads, teams, and use cases where Noma can deliver value, coordinating with Sales when commercial follow-up is needed.
Cross-functional Leadership: Coordinate Customer Engineering, Product, Research, Engineering, Security, and Support resources to move customer plans forward, resolve blockers, and bring customer insights back into us.

our company builds the production-grade AI backbone for top-tier enterprises. We don't just wrap LLMs. Our platform autonomously handles mission-critical workflows, replacing operational friction with seamless, predictive experiences. We are a lean, engineering-driven company working directly with the biggest players in the market.
An FDE at our company is a customer-embedded engineer who owns the technical success of an AI deployment end to end. You don't advise and hand implementation to someone else. You are the implementation owner. You take an ambiguous business problem, break it into solvable technical components, build the solution on our platform, and stay with it until it works reliably in production.
What You'll Do
Own deployments end-to-end. From signed deal to production go-live and stabilization. No hand-offs.
Build production AI agents. Design and ship agent flows on our platform: prompt engineering, orchestration, edge cases, and the testing discipline that makes them production-grade.
Integrate into brownfield reality. Legacy systems, APIs, CRMs, telephony and customer infrastructure, while navigating security, compliance and incomplete requirements.
Debug in environments you don't control. When production misbehaves inside the customer's stack, you find it and fix it.
Push back with judgment. Challenge poor requirements, find creative alternatives, and align technical and business stakeholders behind them.
Be embedded with customers. On-site several days a week during active deployments, often as the most senior technical person in the room. On-site days carry dedicated compensation on top of your salary, and every production go-live carries a milestone bonus.

We are looking for a Product-Driven Senior Software Engineer who wants to do more than build features from a backlog. In this role, you will own entire product surfaces end-to-end - from concept to production - shipping AI-powered features that users actually touch.
Youll work directly with LLMs, APIs, and modern full-stack technologies to build experiences that feel polished, fast, and intelligent.
If you care about how something works as much as that it works, and you want to shape products that matter, this role is for you.
What Youll Do
Own features end-to-end: Design, build, and ship complete product experiences - frontend, backend, and AI integration. No hand-offs.
Build with AI: Integrate LLMs and AI APIs into real product workflows, including prompt engineering, API orchestration, and intelligent UX patterns.
Ship with taste: Make decisions about UX, polish, and user experience. Attention to detail matters.
Move fast: Work in short cycles, ship to production, learn from real users, and iterate.
Make calls: Operate with autonomy and make decisions even when information is incomplete.

Required Head of AI Security
As the Head of AI Security, you will be the ultimate authority and strategic leader responsible for securing our AI/ML infrastructure, data pipelines, and deployed models, you will bridge the gap between advanced data science and enterprise-grade security. You will design, implement, and oversee security frameworks that protect our proprietary AI technologies, multi-agent systems, and RAG architectures.
Youll Own:
Our end-to-end AI security strategy across AI/ML infrastructure, data pipelines, LLMs, RAG systems, and autonomous AI agents
Secure-by-design frameworks and security architecture for AI-powered products and platforms
AI threat modeling, adversarial testing, red teaming, and vulnerability management programs
AI governance, internal security policies, and alignment with emerging global AI regulations and standards
Security tooling, automation frameworks, and continuous monitoring capabilities for AI environments
Cross-functional security leadership across Data Science, AI Engineering, Product, Infrastructure, and SecOps teams
Youll Solve:
Protecting AI systems against emerging threats such as prompt injection, model inversion, data poisoning, and training data leakage
Preventing sensitive customer and enterprise data from leaking into training sets or model outputs
Securing complex AI architectures including LLMs, RAG pipelines, and multi-agent systems at scale
Embedding security seamlessly into the ML lifecycle without slowing innovation
Building scalable AI security operations through automation, monitoring, and continuous adversarial testing
Navigating evolving AI governance, compliance, and regulatory requirements across global markets
Youll Impact:
Maintain our reputation as a leader in secure and trustworthy enterprise AI
Build the foundation that allows AI innovation to scale safely and responsibly
Strengthen customer trust by protecting highly sensitive conversational and business data
Create resilient AI systems that can withstand real-world attacks and emerging threat vectors
Drive a security-first AI engineering culture across the organization
Shape the future of AI security, governance, and MLSecOps in a hypergrowth AI company

Were looking for a Brand and Motion Designer to join our core team and build the engine behind AI-native security. We aren't just building another dashboard, we are architecting a system that processes massive data streams and pushes AI models to their absolute limits to outthink modern attackers. If you are a builder at heart who thrives on high-scale challenges, ownership, and the fast pace of an early-stage startup, youll fit right in.
What You'll Do
Own the visual layer of our GTM motion, from website pages and campaign assets to LinkedIn creative, email, and conference experiences.
Build a repeatable design infrastructure: templates, component libraries, and brand guidelines that let sales, marketing, and product ship on-brand work.
Design the materials that carry our story: sales decks, one-pagers, proposals, marketing content, case studies, and event collateral that make enterprise buyers take us seriously.
Use AI tools to compress the design cycle, then productize what works into workflows the rest of the team can run themselves.
Partner with R&D, marketing, and design on soft UI work wherever the product meets the brand.
Evolve and defend the company brand as we scale, keeping it consistent across every surface and every team that touches it, and wowing audiences and stakeholders along the way.
Turn product highlight into a stuning visual story.