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We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.

we are a leading platform for Trust & Safety teams worldwide, leveraging cutting‑edge AI and world‑class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever‑changing threat landscape.
Were seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic.
Key Responsibilities
Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
Develop, deploy and integrate AI solutions and agentic frameworks, creating both command‑line tools and interactive notebooks that support our teams research and workflow automation needs.
Build and manage data pipelines and databases (SQL) for large‑scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
Integrate research into production by implementing the latest generative AI advancements (including white‑box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings
Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end‑to‑end processes for prompt generation, labeling, and response evaluation.

We're looking for an exceptional, hands-on leader-engineer to join our core engineering team as a true force multiplier and technological anchor for the company. You'll have the flexibility to drive high-impact initiatives from conception to production, own complex technical and AI domains end-to-end, or guide and level up a focused delivery team, operating with a high degree of autonomy in an ambiguous, fast-moving environment.
What You'll Do:
Drive strategic initiatives: lead complex technical projects, AI feature developments, and core architectural components with an ownership mindset.
Architect for AI & data at scale: design robust, scalable infrastructure and pipelines capable of handling massive volumes of cloud infrastructure data.
Bridge product, AI & tech: collaborate closely with Product Managers and data specialists to translate business roadmaps into high-performance technical systems.
Promote engineering excellence: establish development guidelines, lead design and architecture reviews, and raise the bar for code quality across teams.
Mentor & guide: act as a technical mentor to fellow engineers through hands-on collaboration, deep code reviews, and architectural consultation.

We're looking for a Senior Product Manager to own TokenShift, PointFive's product for finding and cutting wasted AI token spend. This is a chance to define product strategy for a brand-new category, working hands-on with R&D on how AI agents and LLM models actually run, get monitored, and get paid for in production. You'll take TokenShift from early adoption to a core pillar of PointFive's platform, alongside our flagship DeepWaste product.
What You'll Do:
Own the product strategy and roadmap for TokenShift, from discovery through GA and beyond.
Translate a deep technical understanding of how AI agents and LLM workloads run, inference calls, endpoints, agent harnesses and orchestration, into requirements R&D can build against.
Partner with R&D, design, and data science to scope, prioritize, and ship features that surface and reduce AI token waste.
Work directly with enterprise customers and prospects to understand how they deploy AI agents in production and where their cost and visibility gaps are.
Define and track success metrics, adoption, cost savings, detection accuracy, and use them to drive roadmap decisions.
Collaborate with go-to-market teams on positioning, messaging, and launch plans for new capabilities.
Stay current on the landscape: coding agents and harnesses, LLM gateways and routers, AI observability, and endpoint management.
Represent the voice of the customer internally, balancing technical depth with business impact.

we are looking for a AI Data Lead.
As Data Lead, you will own how data gets turned into decisions across the company - and lead the shift from traditional BI into AI-driven BI, powered by agents that surface insight in real time. You'll work closely with one data engineer today, with room to grow the team as scope expands.
You'll define what the data function looks like when AI is embedded in it, not bolted on - from the underlying infrastructure to the dashboards and agents people actually use. The playbook for AI-native BI is still being written, and you'll write a lot of it.
Key Responsibilities
Data Strategy & Ownership:
Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI
Set priorities in partnership with senior leadership
Work closely with a data engineer today, with the option to grow the team as the function scales
AI-Driven BI & Agents:
Drive adoption of AI across data workflows - from automating analyses to agents answering business questions in real time
Own the semantic and metrics layer so every dashboard and every agent reads the same definitions
Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents
Expose our data to agents over MCP so business questions get answered without waiting for a dashboard
Define where AI speeds things up - and where human judgment still has to hold the line
Infrastructure & Analytics:
Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability
Lead complex analytics work, A/B testing, and impact measurement, hands-on
Define evals and quality metrics for AI features and agents - not just A/B tests on dashboards
Cross-functional Collaboration
Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions
Represent the data function to the organization - senior-level storytelling with data

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.

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.

Additional details:


You'll design the architecture that lets AI run compliance at scale.
Sedric is the AI compliance platform for financial services. Our agentic AI automates oversight across customer communications and marketing - Real-Time guardrails on calls, pre-approval review on every marketing asset, and post-publication monitoring across partners and channels. Because every customer gets a dedicated compliance model, accuracy goes up, false positives go down, and compliance teams move faster without taking on more risk.
AI isnt a feature at Sedric - its the product. Every agent, LLM flow, and retrieval pipeline that runs a customers compliance program runs on backend systems someone has to design, build, and keep fast, accurate, and cost-efficient at scale.
Were looking for a hands-on AI Engineer who designs those systems and writes the code. Youll own the architecture of our AI backend end to end, ship it to production, monitor how it performs with real customers, and raise the bar for the engineers around you through code reviews, design reviews, and mentoring.
The mission?
We're at an inflection point. Enterprise financial services clients are signing on, and they need more than a product - they need a platform. That means a unified LLM strategy, an architecture that scales, and an R&D org that moves with the same urgency as the business.
This role reports to the AI team Dev team lead and is based in Tel Aviv (hybrid model).
This is a hands-on engineering role. Its not a research position and not a people-management role. Youll spend most of your time designing and building production systems.

BIRD Aerosystems is seeking a Senior Systems Engineer for our System of Systems project, focused on developing innovative aerospace solutions. You will lead systems integration efforts and ensure seamless functionality across various systems. Responsibilities:
* Own the systems engineering of a complex System of Systems (SoS), maintaining the overall system-level view across multiple interconnected systems and subsystems.
* Translate operational and customer needs into system architecture, clear and verifiable requirements, and system and interface specifications.
* Define and manage interfaces and cross-system dependencies across radar, electro-optic, software and hardware teams.
* Lead system integration, verification and validation activities, including system-level troubleshooting and resolution of technical issues, and participate in field integration and test campaigns (ground and live-fire test events).
* Identify system risks, interface gaps and integration challenges early, and drive technical solutions with the relevant engineering teams.
* Participate in and contribute to system design reviews (SRR, PDR, CDR) and technical trade-off studies from a System of Systems perspective.
* Serve as the technical focal point for system-level and cross-system topics, working closely with multidisciplinary engineering teams and reporting key progress, risks and decisions to the Head of Systems Engineering.

At Infinidat, a Lenovo company, we empower enterprises and service providers with cutting-edge storage platforms that redefine performance, reliability, and cyber resilience at scale. If you are a passionate and talented developer and have the capability to be among the best, we invite you to join our journey of success as a Software Team Leader in the NAS Group.

Responsibilities:

* Lead a team of 2-8 developers
* C++ coding over Linux in a multi-threaded, clustered and performance-oriented server-side environment.
* Technical-related aspects of Infinidat’s core component.
* Filesystem IO flow performance improvements.
* High level & detailed design of new features.
* Legacy code maintenance and refactoring.