About the Role

Abnormal AI is looking for a Senior Backend Engineer to join the App Foundations team. App Foundations owns the core customer-centric data and platform services that every Abnormal product depends on — our MPP API and customer data model, the Notifications Platform, License Entitlement, Package Management, Large Model Service (LMS, our internal LLM inference platform), and the MPP Go Service that sits behind our Portal. If a product at Abnormal is launching, scaling, or talking to a customer, it’s almost certainly running on something we own.

This is a senior IC role for a generalist backend engineer who wants to own systems end-to-end, raise the technical and operational bar, and help shape how a platform team operates in an AI-native company. You’ll rotate across our surfaces rather than specializing in one — which means your first year spans API design, distributed systems reliability, LLM inference infrastructure, and the kind of hard, cross-team platform work that determines whether new products ship cleanly.

The ideal candidate is a product-minded, principle-first engineer who takes extreme ownership, communicates crisply, and treats AI tools as a core part of how they build — not a side experiment.

What you will do

• Design, build, and operate high-performance, low-latency services across the App Foundations portfolio — Python/Django, Go, MySQL/PostgreSQL, Kafka, Redis, and ElasticSearch — in close partnership with engineers, designers, PMs, and EMs across R&D.
• Lead end-to-end delivery of platform features and stability workstreams — from tech design and PRR through launch, post-launch ops, and long-term ownership.
• Raise the operational bar: drive SLO-backed reliability work on Tier-0 systems like Notifications and LMS, improve our observability and on-call posture, and reduce unplanned work on the systems you own.
• Contribute to our LLM inference platform (LMS) — model routing and fallback, provider integrations (Azure OpenAI, Bedrock), batch/async inference, cost attribution, and the safety rails that let product teams ship AI features without reinventing the stack.
• Build AI-native internal tools that change how the team operates: automated ticket triage, on-call copilots, post-mortem drafting, customer-request classifiers — following the precedent of our Nora workflow and existing Claude skills.
• Mentor other engineers, drive tech design and PR reviews, and be a credible SME for the systems you own.
• Partner with product managers, TPMs, and peer platform teams (Portal, Customer Journey, Data Security, FedRAMP) to land complex cross-team initiatives cleanly.
• Participate in hiring: write questions, run loops, and help bring the next wave of AF engineers on board.

AI-Forward Hiring

App Foundations is an AI-native team. We expect every engineer — from Day 1 — to use AI coding tools (Cursor, Claude Code, and the rest) as the default way they write and review code, and to design AI leverage into the workflows they own. This role is explicitly for someone who already operates this way and wants to push it further.

In interviews, we’ll look for concrete evidence that you:

• Use AI tools daily to ship faster — and can talk specifically about where they help, where they hurt, and how you’ve adjusted your workflow.
• Have built or shipped something AI-powered beyond the IDE — a script, an agent, a workflow automation, a production feature — that actually changed how work got done.
• Think at the workflow level, not just the keystroke level: you look at an ops process, a support queue, or a team ritual and ask “what should an agent own here?”
• Have opinions about how AI changes the role of a senior engineer in the next 1–3 years, and are excited about a team that treats AI as core infrastructure rather than an experiment.

Because we own LMS, experience building with LLMs in production — provider APIs, evals, model routing, cost and quota management — is a strong plus, but not required.

Must Have Skills

• 5+ years of backend software engineering experience building and operating production services at scale.
• 4+ years on relevant tech stacks — Python (Django) and/or Go; MySQL / PostgreSQL; and hands-on experience with Kafka, Redis, and ElasticSearch.
• 3+ years supporting enterprise-class customers in production, including ownership of SLOs, on-call, and incident response.
• 2+ years of system design experience — demonstrated ability to design, document, and land non-trivial cross-team architectures.
• Proven experience leading multi-quarter projects end-to-end: tech design, implementation, launch, and post-launch operations.
• Demonstrated daily use of AI coding tools in your current workflow, and specific examples of where you’ve used AI to improve how you or your team works beyond just code generation.
• Strong written and verbal communication; proven ability to collaborate autonomously and asynchronously with remote stakeholders.
• Bachelor’s degree in Computer Science or equivalent professional experience.

Nice to Have

• Hands-on experience building with LLMs in production — provider APIs (OpenAI/Anthropic/Bedrock), model routing and fallback, evals, batch inference, or cost/quota tooling.
• Experience with notification delivery systems, licensing/entitlement platforms, or other high-leverage internal platforms used by many product teams.
• Experience building and shipping AI agents or automations (coding agents, ops agents, classifier pipelines) that replaced meaningful manual work.
• Experience mentoring engineers and acting as a tech lead on at least a small squad.
• Master’s degree in Computer Science or a related field.

#LI-AJ1

About the Role

Abnormal AI is looking for a Senior Backend Engineer to join the App Foundations team. App Foundations owns the core customer-centric data and platform services that every Abnormal product depends on — our MPP API and customer data model, the Notifications Platform, License Entitlement, Package Management, Large Model Service (LMS, our internal LLM inference platform), and the MPP Go Service that sits behind our Portal. If a product at Abnormal is launching, scaling, or talking to a customer, it’s almost certainly running on something we own.

This is a senior IC role for a generalist backend engineer who wants to own systems end-to-end, raise the technical and operational bar, and help shape how a platform team operates in an AI-native company. You’ll rotate across our surfaces rather than specializing in one — which means your first year spans API design, distributed systems reliability, LLM inference infrastructure, and the kind of hard, cross-team platform work that determines whether new products ship cleanly.

The ideal candidate is a product-minded, principle-first engineer who takes extreme ownership, communicates crisply, and treats AI tools as a core part of how they build — not a side experiment.

What you will do

• Design, build, and operate high-performance, low-latency services across the App Foundations portfolio — Python/Django, Go, MySQL/PostgreSQL, Kafka, Redis, and ElasticSearch — in close partnership with engineers, designers, PMs, and EMs across R&D.
• Lead end-to-end delivery of platform features and stability workstreams — from tech design and PRR through launch, post-launch ops, and long-term ownership.
• Raise the operational bar: drive SLO-backed reliability work on Tier-0 systems like Notifications and LMS, improve our observability and on-call posture, and reduce unplanned work on the systems you own.
• Contribute to our LLM inference platform (LMS) — model routing and fallback, provider integrations (Azure OpenAI, Bedrock), batch/async inference, cost attribution, and the safety rails that let product teams ship AI features without reinventing the stack.
• Build AI-native internal tools that change how the team operates: automated ticket triage, on-call copilots, post-mortem drafting, customer-request classifiers — following the precedent of our Nora workflow and existing Claude skills.
• Mentor other engineers, drive tech design and PR reviews, and be a credible SME for the systems you own.
• Partner with product managers, TPMs, and peer platform teams (Portal, Customer Journey, Data Security, FedRAMP) to land complex cross-team initiatives cleanly.
• Participate in hiring: write questions, run loops, and help bring the next wave of AF engineers on board.

AI-Forward Hiring

App Foundations is an AI-native team. We expect every engineer — from Day 1 — to use AI coding tools (Cursor, Claude Code, and the rest) as the default way they write and review code, and to design AI leverage into the workflows they own. This role is explicitly for someone who already operates this way and wants to push it further.

In interviews, we’ll look for concrete evidence that you:

• Use AI tools daily to ship faster — and can talk specifically about where they help, where they hurt, and how you’ve adjusted your workflow.
• Have built or shipped something AI-powered beyond the IDE — a script, an agent, a workflow automation, a production feature — that actually changed how work got done.
• Think at the workflow level, not just the keystroke level: you look at an ops process, a support queue, or a team ritual and ask “what should an agent own here?”
• Have opinions about how AI changes the role of a senior engineer in the next 1–3 years, and are excited about a team that treats AI as core infrastructure rather than an experiment.

Because we own LMS, experience building with LLMs in production — provider APIs, evals, model routing, cost and quota management — is a strong plus, but not required.

Must Have Skills

• 5+ years of backend software engineering experience building and operating production services at scale.
• 4+ years on relevant tech stacks — Python (Django) and/or Go; MySQL / PostgreSQL; and hands-on experience with Kafka, Redis, and ElasticSearch.
• 3+ years supporting enterprise-class customers in production, including ownership of SLOs, on-call, and incident response.
• 2+ years of system design experience — demonstrated ability to design, document, and land non-trivial cross-team architectures.
• Proven experience leading multi-quarter projects end-to-end: tech design, implementation, launch, and post-launch operations.
• Demonstrated daily use of AI coding tools in your current workflow, and specific examples of where you’ve used AI to improve how you or your team works beyond just code generation.
• Strong written and verbal communication; proven ability to collaborate autonomously and asynchronously with remote stakeholders.
• Bachelor’s degree in Computer Science or equivalent professional experience.

Nice to Have

• Hands-on experience building with LLMs in production — provider APIs (OpenAI/Anthropic/Bedrock), model routing and fallback, evals, batch inference, or cost/quota tooling.
• Experience with notification delivery systems, licensing/entitlement platforms, or other high-leverage internal platforms used by many product teams.
• Experience building and shipping AI agents or automations (coding agents, ops agents, classifier pipelines) that replaced meaningful manual work.
• Experience mentoring engineers and acting as a tech lead on at least a small squad.
• Master’s degree in Computer Science or a related field.

#LI-AJ1

About the Role

The Dev Accelerator team builds and operates Abnormal’s internal developer platform: the tools, libraries, and infrastructure that help engineers design, build, test, and ship products quickly and safely. The team owns developer CLI tooling, monorepo build and CI workflows, shared Go/Python libraries, and test and release safety systems that form the Golden Path for backend development.

As a Software Engineer on Dev Accelerator, you’ll own scoped problems end-to-end with support from teammates, using good judgment and growing independence to deliver reliable outcomes. You’ll use AI as a core part of how you explore solutions and move quickly, while validating that generated outputs are correct, maintainable, and production-ready.

What you will do 

• Contribute to the internal developer platform that supports backend development across the company, from local developer workflows to shared services and libraries.
• Build and improve scoped pieces of developer tooling, including CLI and scaffolding workflows that help engineers create and ship new services safely and consistently.
• Help maintain and improve CI/CD, linting, and testing workflows in the monorepo, with a focus on reliability, fast feedback, and keeping main healthy.
• Contribute code to shared Go and Python libraries and services, learning the team’s patterns for safe, maintainable, and consistent usage.
• Use AI to explore approaches, automate repetitive work where appropriate, and iterate on implementations until they meet real production standards.
• Debug issues, write tests, and validate behavior in real environments rather than relying only on generated output or assumptions.
• Improve team documentation, examples, and shared context so both engineers and AI tools can produce better results over time.

Must Haves 

• 1+ years of professional development experience or 2+ years of consistent open source contributions
• Relevant software engineering experience through internships, co-ops, research, open-source work, substantial project work, or early-career full-time roles that demonstrate readiness to contribute in a production environment.
• Strong software engineering fundamentals and the ability to write, test, debug, and improve production-quality code.
• Experience with Python or Go, plus willingness to learn whichever language is less familiar for the role.
• Familiarity with modern development workflows such as version control, code review, testing, and CI/CD.
• Good judgment when using AI tools for engineering work: you can evaluate outputs, catch incorrect or incomplete solutions, and refine them to fit real system constraints.
• Comfort taking ownership of scoped problems end-to-end, asking for help when needed, and steadily increasing independence.
• Strong learning mindset, adaptability, and openness to feedback in a fast-moving platform environment.
• Clear communication and a collaborative approach to working with teammates and internal customers.

Nice to Have 

• B.S. degree in computer science or related field
• Internship, co-op, or early-career experience building internal tools, backend services, or developer productivity tooling.
• Exposure to monorepo development, CI/CD pipelines, or build systems.
• Familiarity with Go/Python shared libraries, gRPC/Protobuf APIs, or cloud-based backend systems.
• Interest in developer experience, self-service platforms, or Golden Path tooling.
• Curiosity about AI-native developer workflows and excitement about improving how engineers build software with AI.

#LI-AJ1

About the Role

The Dev Accelerator team builds and operates Abnormal’s internal developer platform: the tools, libraries, and infrastructure that help engineers design, build, test, and ship products quickly and safely. The team owns developer CLI tooling, monorepo build and CI workflows, shared Go/Python libraries, and test and release safety systems that form the Golden Path for backend development.

As a Software Engineer on Dev Accelerator, you’ll own scoped problems end-to-end with support from teammates, using good judgment and growing independence to deliver reliable outcomes. You’ll use AI as a core part of how you explore solutions and move quickly, while validating that generated outputs are correct, maintainable, and production-ready.

What you will do 

• Contribute to the internal developer platform that supports backend development across the company, from local developer workflows to shared services and libraries.
• Build and improve scoped pieces of developer tooling, including CLI and scaffolding workflows that help engineers create and ship new services safely and consistently.
• Help maintain and improve CI/CD, linting, and testing workflows in the monorepo, with a focus on reliability, fast feedback, and keeping main healthy.
• Contribute code to shared Go and Python libraries and services, learning the team’s patterns for safe, maintainable, and consistent usage.
• Use AI to explore approaches, automate repetitive work where appropriate, and iterate on implementations until they meet real production standards.
• Debug issues, write tests, and validate behavior in real environments rather than relying only on generated output or assumptions.
• Improve team documentation, examples, and shared context so both engineers and AI tools can produce better results over time.

Must Haves 

• 1+ years of professional development experience or 2+ years of consistent open source contributions
• Relevant software engineering experience through internships, co-ops, research, open-source work, substantial project work, or early-career full-time roles that demonstrate readiness to contribute in a production environment.
• Strong software engineering fundamentals and the ability to write, test, debug, and improve production-quality code.
• Experience with Python or Go, plus willingness to learn whichever language is less familiar for the role.
• Familiarity with modern development workflows such as version control, code review, testing, and CI/CD.
• Good judgment when using AI tools for engineering work: you can evaluate outputs, catch incorrect or incomplete solutions, and refine them to fit real system constraints.
• Comfort taking ownership of scoped problems end-to-end, asking for help when needed, and steadily increasing independence.
• Strong learning mindset, adaptability, and openness to feedback in a fast-moving platform environment.
• Clear communication and a collaborative approach to working with teammates and internal customers.

Nice to Have 

• B.S. degree in computer science or related field
• Internship, co-op, or early-career experience building internal tools, backend services, or developer productivity tooling.
• Exposure to monorepo development, CI/CD pipelines, or build systems.
• Familiarity with Go/Python shared libraries, gRPC/Protobuf APIs, or cloud-based backend systems.
• Interest in developer experience, self-service platforms, or Golden Path tooling.
• Curiosity about AI-native developer workflows and excitement about improving how engineers build software with AI.

#LI-AJ1

About the Role

We’re looking for a Technical Program Manager who excels at driving execution for AI-driven SaaS products. This is a unique yet exciting opportunity to join and contribute to Abnormal's Research & Development Operating System. The creation of predictable, reliable, and standardized R&D processes is crucial for Abnormal's future strategy and success. To continue thriving in business, Abnormal is focused on developing several new products and features leveraging AI technologies. Technical Program Managers will provide a consistent framework and fabric of execution as a foundation for executing these products.

In this role, you’ll partner closely with Product and Engineering teams to architect, define, and execute systems that ensure programs run predictably, efficiently, and with high visibility.

The ideal profile thrives in an entrepreneurial environment, handling competing priorities and ambiguity with confidence. You have a growth mindset and are a quick and keen learner.  

In this job, you will bring these skills

• Project / Program Management & Organization: Excellent project manager with delivering large cross functional complex projects. Able to take complex technical requirements and translate into program plans. 
• Exceptional communicator: Able to effectively collaborate with both technical and non-technical stakeholders in both written and verbal form.
• Works well in ambiguity: Ability to be a kickstarter especially in this initial Engine building phase.
• Ownership: Goal-oriented with an ownership mentality. Ability to self-organize, pull in resources with clear expectations and drive successful outcomes
• Continuous improvement: Committed to personal and professional growth, with a constant desire to improve, create value, and make your team better. Growth mindset and grit will be key traits to success.
• Technical Capabilities: Leverage a technical background to support engineering in technical design and gain credibility.

Role Responsibilities

• Translate complex technical requirements from Product Engineering, Platform and Infrastructure Engineering, ML Engineering, and other critical stakeholders into program plans with clearly defined milestones, owners, and deadlines
• Drive programs and manage project schedules by determining dependencies across project teams, proactively addressing risks, and reporting progress to stakeholders to ensure on-time delivery of program deliverables
• Participate in technical strategy development and resource planning with engineering and product partners
• Build strong relationships with key stakeholders to drive alignment and progress toward shared goals
• Design, establish, and iterate on best practices and repeatable processes for operational excellence, including incident management and leading post-mortem's 

Qualifications: 

• One to Three (1-3) years of professional experience in Technical Program or Project Management
• A Bachelor's degree in Engineering or a closely related discipline
• Experience with product lifecycle management and product operations best practices
• Experience working with SaaS products like Jira and an understanding of SQL
• Experience working in iterative, fast-paced weekly release environments, leveraging agile and scrum processes for planning, execution, and delivery."
• Capable of translating and communicating highly technical requirements in pragmatic & in a way that focuses on customer or business-impact
• Curiosity for AI-first security products and a desire to influence how they reach customers successfully.

#LI-EM5

The Opportunity

Abnormal AI is redefining cybersecurity with an AI-native platform that protects modern enterprises from advanced email attacks, account compromise, and human-targeted threats. Our products help security teams detect sophisticated attacks, investigate risk quickly, and automate response at enterprise scale.

We’re building a team of strong engineers who are excited to use modern AI development tools to build faster, make better decisions, and ship high-quality software with more leverage.

We’re looking for a Software Engineer II - Backend to join our Customer Journey Team. This is an opportunity to work on core backend systems that shape how customers get onboarded onto the Abnormal platform—making the process smoother, faster, more automated, and increasingly self-serve.

The Customer Journey team builds the product and platform experiences that help customers get onboarded quickly and successfully. We solve onboarding problems by reducing manual work, improving reliability, and making complex setup flows easier for customers and internal teams. The team owns the workflows, automation, and visibility needed to move customers from initial setup to full activation. As a SWE2, you will build scalable systems and user experiences that improve onboarding quality, speed, and time-to-value.

If you’re excited by backend engineering, large-scale distributed systems, high-reliability services, and AI-augmented development, this is a high-impact opportunity to help shape a foundational part of Abnormal’s customer experience.

What You’ll Do

• Abnormal’s engineering expectations emphasize strong judgment in using AI to explore solutions, refine outputs, and deliver reliable production outcomes.

• Leverage AI-Augmented Development to enhance productivity, optimize workflows, and automate repetitive tasks.

• Build backend services and workflows that make POV onboarding smoother, quicker, and more self-serve for customers.

• Design scalable systems that provide end-to-end visibility across onboarding processes and reduce dependency on downstream modules.

• Develop and improve core backend systems across tenant management, onboarding orchestration, setup tooling, and command center experiences.

• Collaborate with strong engineers and cross-functional partners to deliver impactful solutions for customers and internal teams.

• Build reliable APIs and backend architectures that support enterprise-grade onboarding workflows at scale.

• Take ownership of features end-to-end, from design and implementation through testing, rollout, and production validation.

Must Haves

• 3+ years of professional experience in software development.

• Backend development experience with Python and/or Golang.

• Experience with AI development tools such as Cursor, GitHub Copilot, or Claude.

• Experience or passion for building scalable, enterprise-grade applications.

• Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

• Strong fundamentals in computer science, data structures, debugging, and performance optimization.

Nice to Have

• Experience building onboarding, provisioning, workflow orchestration, or platform automation systems.

• Familiarity with backend systems that provide process visibility, status tracking, or operational tooling.

• Experience with distributed systems, service-oriented architectures, or event-driven workflows.

• Exposure to tenant lifecycle management, setup automation, or enterprise SaaS platform workflows.

• Experience improving service reliability, resiliency, and observability in production systems.

• Experience working on cybersecurity, enterprise SaaS, or customer-facing platform products.

Ready to be part of AI transformation at Abnormal Security? Apply Now!

Once you apply, you’ll be invited to our AI-Augmented Development Challenge, where you’ll gain hands-on experience with AI-powered tools like Cursor and Copilot to build real-world application features. This challenge is a take-home assignment, requiring 2-4 hours of work to be completed within one week - apply when you’re ready!

Job Description

Abnormal AI is revolutionising cybersecurity by leveraging AI-native technologies to combat modern cyber threats. Behind every fast-moving go-to-market motion is a platform that makes it possible — and that's what the AI GTM Platform team builds. We're the engineering team powering the forward-deployed product teams who sit shoulder-to-shoulder with our customers and internal stakeholders, turning enterprise pain points into shipped product on timelines traditional enterprise cycles can't match.

If you love building leverage — tools, systems, and platforms that multiply the impact of others — and want to own products through every stage of their lifecycle, this role is for you.

What You'll Do as a Software Engineer II

As part of the AI GTM Platform team, you will:

• Build the platform that powers the field. Design and ship the internal products, APIs, and services that let our forward-deployed teams prototype, validate, and scale customer-facing solutions with unusual speed.
• Own the full product lifecycle — 0→1, 1→10, and 10→100. You'll work across Experimental, Early Access, and General Availability stages of platform products. It's rare to get to take an idea from a napkin sketch through enterprise-grade rollout; here, you'll do it, sometimes on multiple products in parallel.
• Work in one of the most dynamic problem spaces in the business. GTM is where strategy, customers, product, and revenue converge. Every customer interaction, every deal, every expansion flows through it — and the platforms you build shape how effectively all of that moves.
• Leverage AI-augmented development. Use AI coding assistants to enhance productivity, optimise workflows, and automate repetitive work.
• Combat modern cyber threats at scale. Build secure, scalable systems that sit inside a platform processing billions of security events for Fortune 500 enterprises.
• Partner closely with customers and the field. Work with the people closest to our enterprise customers to understand real problems, iterate quickly, and deliver solutions that compound over time.

Technical Requirements

We're looking for engineers who have:

• 4+ years of professional experience in software development.
• Backend development experience with Python, TypeScript, or Go.
• Solid fundamentals in at least one modern frontend framework (React, Angular, or Vue). AI accelerates a lot of the implementation work here — what matters is that you can read generated code critically, tell good patterns from bad, and ship frontends you'd be comfortable defending in review.
• Familiarity with — or genuine curiosity and willingness to learn — AI coding assistants as part of your everyday workflow.
• Experience or strong interest in building scalable, enterprise-grade applications.
• Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Strong fundamentals in computer science, data structures, and performance optimisation.

Nice to Have

• Experience building internal platforms, developer tools, or systems used by other engineering and product teams.
• Background in taking products through multiple maturity stages (prototype → pilot → scale).
• Exposure to GTM, sales engineering, solutions engineering, or other customer-facing engineering environments.

Why Abnormal Security — and Why This Team

• A rare breadth of surface area. Most platform roles specialise in one stage of maturity. Here, you'll operate across experimental prototypes, early-access pilots with design partners, and fully productised GA systems — and learn how each stage demands a different kind of engineering.
• Build for the sharpest users you'll ever have. Your internal users are the technical, fast-moving teams closest to our enterprise customers. They'll give you direct, high-signal feedback and put what you ship into customers' hands quickly.
• Direct line to business impact. GTM platforms are measured by how much faster the business moves as a result. Your work compounds across every customer engagement, every quarter.
• AI-native engineering culture. We expect AI-assisted development — it's how we stay small, fast, and ambitious. You'll have real room to experiment with and shape how the team uses these tools.
• Mission that matters. The systems you build ultimately protect the world's largest enterprises from sophisticated cyber attacks.

Ready to be part of the AI transformation at Abnormal Security?

Once you apply, you'll be invited to our AI-Augmented Development Challenge, where you'll gain hands-on experience with AI coding assistants to build real-world application features. This challenge is a take-home assignment requiring 2–4 hours of work to be completed within one week — apply when you're ready!

#LI-JP2

About the Role

This is a Bay Area based role with periodic onsite requirements. You should expect to work onsite in the Bay Area for designated periods throughout the year as required by the business, which may include consecutive weeks or months, totaling approximately 25% of working time annually.

Enterprises are undergoing two simultaneous transformations: moving critical infrastructure to the cloud and adopting AI agents at scale. Both create an identity explosion—humans, service accounts, and AI agents now outnumber traditional users 10-to-1, each with permissions that legacy tools can't govern. Abnormal's Identity Security team is building the platform to secure this new reality: unified visibility across all identity types, behavioral intelligence that understands what's normal, and AI-native automation that operates at cloud speed. We're extending the same behavioral approach that made Abnormal the leader in email security to protect identities across cloud infrastructure and AI systems.

What you will do

• Build discovery, classification, monitoring, and protection for machine identities and their agentic actions.
• Ship guardrails and policy engines that enable safe automation while preventing misuse, escalation, and anomalous behavior.
• Create high‑availability pipelines that ingest and correlate identity, authorization, and behavioral signals from cloud, SaaS, IAM/SSO, and audit logs.
• Drive 0→1 iteration: prototype quickly, test assumptions, learn from usage, and scale simple solutions.
• Collaborate across security, platform, and data teams; write and review technical designs; and participate in core SDLC rituals.

Must Haves

• 2+ years building software applications.
• Experience productionizing large‑scale, data‑intensive systems.
• High velocity and creativity in solving technical challenges.
• Experience & desire to adopt & improve AI-native development workflows. 
• Strong debugging with logs, metrics, and signals.
• Ability to translate business requirements into high‑quality software.
• Ability to independently solve complex problems and work cross‑functionally.
• BS in CS/SE/IS or related field.

Nice to Have

• Experience with Go and Python.
• Experience in IAM, non‑human/machine identities, secrets management, workload identities, OAuth/OIDC, SCIM, SSO, or policy engines.
• Experience in cybersecurity or related industries.
• Experience with big data, statistics, and ML for identity/behavioral risk modeling.

#LI-NT1