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we are looking for a Head of Product, AI Therapy.
As a Head of Product - AI Therapy, you will own how AI and clinical expertise come together across the product to create a new kind of therapy experience. This role sits at the intersection of consumer product, AI technology, and clinical science - defining what intelligent relationship support looks like when it's grounded in real therapeutic data and validated by real clinicians.
You'll design the conversational AI that supports users between sessions - emotional processing, conversation preparation, reflections, personalized guidance. You'll build the intelligence layer that turns therapy session data into structured relationship context, so every interaction feels informed by the couple's actual journey. And you'll push into open space - new product surfaces, new modes of support, new ways to make therapists more effective - because the category is being created now and the playbook doesn't exist.
This is a hands-on role that requires balancing vision with execution, working closely with our clinical lead, AI engineers, and design team to ship products where every word matters - because people are vulnerable when they use them. In regular collaboration with founders and clinical leadership, you'll shape the AI therapy strategy and help define the future of continuous, tech-enabled relationship support.

We are looking for a Generative AI Engineer to lead our AI efforts end-to-end - from infrastructure and production systems to internal adoption and cross-team enablement.
You will play a significant role in building the world's first Consumer Therapy AI Product (someone said RAG? But we mean a real one that works in production...).
This is a critical role in a high-growth, fast-paced B2C startup, requiring a leader who can advocate for Engineering requirements, tech-debt and best practices while promoting a product-mindset and putting our customers front and center.

we are looking for a Full-Stack Engineer.
Own features end-to-end across our FastAPI + React/TypeScript stack - the catalog, the seller wizard, payments, admin tooling, and the infrastructure layer we're building next.
What you'll do
Design, build, test, and deploy features across the frontend (React + TypeScript) and the backend (FastAPI + PostgreSQL).
Work on what buyers and sellers touch every day - the catalog, the listing wizard, checkout, the seller dashboard, admin tools.
Help build the next phase: hosting and running sellers' apps on our own infrastructure.
Keep the bar high - tests, code review, security-minded by default.

we are looking for a Growth & Community Marketer.
What you'll do:
Own seller recruitment: find indie builders and "vibe coders" in communities, Facebook groups, Discords, and X - and get them to list on SaaStore.
Run our social presence (Instagram, Facebook, X / LinkedIn) and write copy that sounds like us, not like a template.
Plan and run campaigns - organic and paid (Google Ads, Meta) - and read the numbers.
Build relationships with sellers, communities, and anyone who can send us good builders or buyers.
Help shape positioning and messaging across the site, emails, and landing pages.

We are seeking a highly experienced Software Architect to join our team and take ownership of designing and developing complex systems that directly impact our technology. In this role, youll work cross-functionally with R&D teams to build solutions that address critical needs, drive efficiency, and lead meaningful processes within the organization.

Responsibilities
Architectural Design & Strategy: Define and develop scalable and efficient system architectures.
Mentorship & Technical Leadership: Guide and mentor R&D teams, ensuring best practices and high-quality technical decisions.
Raise the Bar - Inspire and guide the team to achieve excellence in software engineering, consistently setting high standards for outstanding delivery.
Cross-functional Collaboration: Work closely with engineering, product, data science teams, and other stakeholders to translate business needs into technical solutions.
Problem Solving: Analyze and resolve complex technical challenges with innovative solutions.
Performance Optimization: Ensure system reliability, scalability, and performance through architectural improvements.

The Senior Backend Engineer team (Data Team) builds the systems that discover, understand, and govern customer data at petabyte scale. We turn raw enterprise data into the security signal the rest of the platform builds on, working on problems like distributed systems running inside customer clouds, analytics over large data lakes, and detection logic that has to be both precise and fast. Youll work end-to-end and ship features that every Sentra customer uses.

Responsibilities
Designing and implementing core components within the classification and policy stack, including microservices, ETLs, and shared libraries.
Owning features end-to-end: design, implementation, rollout, testing, monitoring, and production operation.
Conducting design and code reviews with the team and across R&D.
Driving scale, performance, and cost optimizations against multi-tenant data-lake workloads.
Partnering with AI/ML, Research, Product, and Frontend to ship cross-functional initiatives.

We are looking for a Senior Backend Engineer (AI DLP) to join the team building our next-generation DLP product. The team is extending our data-security platform from understanding sensitive data at rest to protecting it at the moment it is used or shared-including across browsers, GenAI applications, and employee endpoints.

You will help build the control plane behind this product: the services that manage endpoint identity and enrollment, policies, classification, device configuration, telemetry, and the connection between our DSPM intelligence and real-time DLP decisions. This is a role with substantial technical ownership, direct customer impact, and close collaboration across Product, Research, Data, Frontend, and Infrastructure.

Responsibilities
Design and implement core backend components of our DLP control plane.
Own features end-to-end: architecture, implementation, testing, rollout, observability, and production operation.
Build secure, reliable multi-tenant services that communicate with browser extensions and endpoint agents deployed across customer endpoint fleets.
Connect our DSPM classification and policy systems with real-time endpoint enforcement, translating data-at-rest intelligence into actionable protection.
Design APIs and data models that support large endpoint fleets, frequent policy updates, offline clients, credential rotation, and safe software upgrades.
Improve the scalability, performance, reliability, and operational visibility of the DLP platform.
Conduct design and code reviews and help establish strong engineering practices.

We're looking for a DevOps & Deployment to join the Deployment team and take ownership of how we reache our customers' environments - and how it runs once it gets there.

This role sits at the intersection of cloud infrastructure and backend engineering. You'll build and maintain the Infrastructure-as-Code and tooling that customers use to deploy us across AWS, Azure, and GCP - including Kubernetes-based, VM-based, and on-premise environments. Alongside that, you'll develop the backend services that power the deployment lifecycle: orchestration, provisioning, environment management, health monitoring, and deployment verification - time-critical services where reliability directly impacts the customer experience.

The role blends hands-on engineering, cloud architecture, and customer-facing technical work. You'll collaborate with Solutions Engineering, Support, and customers directly to ensure deployments are smooth, secure, and scalable.

Responsibilities
This is a DevOps and Backend role, with approximately 60% of the focus on DevOps & Deployment and 40% on Backend engineering. Youll own both the infrastructure that enables us to run in complex customer environments and the backend services that support and manage the deployment lifecycle.

DevOps & Customer Deployment ~60%
Develop and maintain Infrastructure-as-Code (Terraform, CloudFormation) that customers use to deploy and integrate the product into their cloud environments.
Design customer-deployable cloud architectures across AWS, Azure, and GCP, including networking (VPC/VNet, routing, NAT, PrivateLink / private endpoints) and security primitives.
Build and maintain deployment tooling (CLI tools, installers, templates, automation) to simplify customer setup and upgrades.
Develop and maintain our Kubernetes-based deployment (Golang, Helm) for both cloud-native and on-premises environments.

Backend Engineering ~40%
Build and maintain backend services (Python, TypeScript) that power the deployment lifecycle - including orchestration, provisioning, and environment management.
Develop health monitoring and deployment verification services that ensure reliable, validated deployments with minimal customer friction.
Design and improve APIs that manage customer environments, ensuring they are robust, well-documented, and easy to integrate with.
Own the reliability and performance of time-critical deployment services where latency and correctness directly affect the customer experience.

Collaboration & Customer-Facing Work
Act as a technical escalation point for customer deployment and integration issues, working closely with Solutions Engineering and Support.
Collaborate with external-facing teams (Customer Success, Solutions Engineering, Sales Engineering) on customer deployments and integrations, including participating in calls or troubleshooting sessions when needed - sometimes during US business hours.

We are seeking an experienced Data Science Team Lead to join us and play a key role in shaping the future of data security. As a Data Science Lead, you will be part of our Classification team, which lies at the core of our mission - identifying sensitive data and helping customers detect the most critical risks in their cloud environments. Our multidisciplinary team of data scientists.

Responsibilities
Lead the end-to-end lifecycle (design, development, and deployment) of ML models (e.g., NER, LLMs) to advance our data classification and entity recognition capabilities.
Partner with Product to align cutting-edge AI technologies with real-world customer needs and our roadmap.
Architect robust experimentation frameworks to accelerate model iteration, validation, and production deployment.
Utilize extensive datasets to define quality benchmarks and drive continuous performance improvements.
Champion innovation by identifying opportunities for automation and AI-driven features that maximize customer value.