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We're looking for a Senior Backend Engineer to join the team as a core contributor, owning significant parts of the backend behind these capabilities. The role is backend-first and Go-centric, but you'll also touch the React front end when a feature calls for it - so comfort moving across the stack matters. Quality is a shared responsibility here: our QA partner owns most test automation, but team members regularly pitch in to keep automation coverage moving and avoid bottlenecks.
​How will you make an impact?
Design and develop functional and technical capabilities within Chiron's large-scale, distributed backend systems, making ongoing architecture and design decisions
Take full ownership of features and product areas end-to-end: architecture, coding, testing, CI/CD, and production observability
Build and operate distributed microservices - gRPC/REST APIs, message queues, PostgreSQL-backed services - deployed on Kubernetes
Build and maintain React components/pages (e.g., risk tables, single-risk views) that consume your backend services when a feature requires front-end changes
Partner with our QA team on test automation - pitching in on backend automation in Go and front-end automation in Cypress when needed - to help keep coverage moving and reduce bottlenecks
Use AI-assisted coding tools as part of your day-to-day development workflow, from writing and reviewing code to test generation and debugging
Work smoothly with local and remote, multi-geo R&D and non-R&D teams, maintaining high visibility and effective communication
Provide in-depth technical knowledge, guidance, and mentorship to other team members as needed
Participate actively in design discussions and code reviews, holding the team to high execution and quality standards.

As an MLOps Team Leader, you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.

What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power our AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.

As a Backend Team Leader, you will lead a team of backend and MLOps engineers that owns the systems behind our AI-driven product features. Your team works closest to our AI group - the Algorithms and Data teams - and owns the engineering side of turning models into reliable production capabilities.

Concretely, that means owning real backend architecture - the services and APIs that carry AI-driven capabilities into the product, the data collection pipelines that feed model training, the storage and query layers that hold model outputs and the insights we derive from them, and the validation pipelines that let us trust production flows. You will make the core design decisions on service boundaries, data models, event flows, and scale and cost tradeoffs, in a domain where both the data volume and the correctness bar are high. You do not need to arrive as an ML expert. You do need to be the kind of engineer who walks into an unfamiliar domain, learns it properly, and starts making good decisions in it.

What you'll be doing -

Lead and grow the team
Manage backend and MLOps engineers, some embedded in product pods; coach on delivery, decision-making, and career growth
Set clear expectations for ownership and quality; track progress against team goals, surfacing risks early.

Own the backend behind our AI features
Build and scale data pipelines with the AI group, and design how model insights are stored, queried, and exposed to the product
Build validation pipelines and partner with the Algo team to take models from experiment to production.

Drive architecture direction and alignment
Align backend decisions with the wider group, guide design discussions, and keep specs and plans on time
Collaborate with the platform team on infrastructure, deployment, and reliability standards.

Improve reliability and operational readiness
Raise the bar on stability, observability, and alert quality
Turn recurring issues into focused engineering work; lead debriefs and drive action items to completion.

As Backend Platform Team Leader, you'll lead the Platform pod. The pod owns our shared backend infrastructure (Kubernetes, Redpanda (Kafka), RabbitMQ, CI/CD, observability, and more), and it builds the tools, architecture and agentic workflows that let engineers in every other pod ship faster and more safely, at our growing scale

The role has two parts. As Pod Lead, you own the pod's direction, planning, delivery, and working process. As People Manager, you own the growth and performance of 3-4 direct reports, some of whom may work in other pods.

What you'll be doing -
Infrastructure Ownership: Keep our shared infrastructure reliable, secure, and cost-efficient, and make every change to it safe and well planned.
Architectural Evolution: Lead multi-quarter programs that reshape our backend, and migrate services onto them safely.
Reliability: Make sure problems surface early, and drive incidents to their real root cause.
Direction and Delivery: Maintain one clear, prioritized plan that you know in depth, and run a predictable team.
Planning and Delivery: Own sprint and quarter planning. Maintain one clear, prioritized plan that you know in depth, and run a predictable team.
Pod Process: Follow the PDLC, uphold the company's working processes and policies, and continuously shape and improve how the pod works.
Technical Ownership: Know the pod's systems and how they fit together deeply enough to reason about them with confidence, guide design decisions, and challenge assumptions.
People Leadership: Set clear goals and expectations, give honest feedback, invest in each report's growth, and stand behind your people. Where your reports work in other pods, stay aligned with those pod leads.

We're looking for a Recruiter to join our team. This is a maternity leave replacement for a 1-year contract with the possibility of extension.

What will you do:
Partner with our talent team and hiring managers to gain a deep understanding of our hiring needs for Product and R&D roles across Israel and the US.
Source top-tier candidates by utilizing a variety of channels and creative techniques, including social media, professional networks, and targeted outreach.
Screen resumes and conduct initial phone assessments to evaluate candidates' skills, qualifications, and alignment with our company culture.
Manage the interview process, including coordinating and scheduling interviews and ensuring a seamless and positive experience for every candidate.
Lead behavioral and HR interviews to assess candidate motivation, core competencies, and cultural alignment, complementing the technical assessments performed by hiring managers.
Utilize our applicant tracking system (ATS) to maintain accurate candidate records and track progress.
Build and nurture a strong talent pipeline for current and future hiring needs.
Stay up to date on industry trends, market conditions, and best practices in talent acquisition.

Alice is hiring Intermediate Malware Researchers to analyze and review malware applications. Candidates should have a background in cybersecurity and software development. The role includes training in malware analysis and detection and provides exposure to various malware threats and techniques. Researchers will combine technical and intelligence findings to reach accurate verdicts and assist in the bulk removal of malicious applications. The position requires adaptability and proactive identification of emerging malware trends. We are seeking candidates who are willing to learn, can perform effectively under pressure, and maintain high professional standards.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!