דרושים » תוכנה » Specialist Portfolio Manager

We are seeking an experienced and highly motivated Team Lead to lead our Data Infrastructure team. This role is responsible for managing a team of engineers while driving the design, scalability, reliability, and operational excellence of the companys core data platform.
The ideal candidate combines strong technical expertise in distributed systems and data technologies with proven leadership capabilities, strategic thinking, and the ability to lead complex initiatives end-to-end - from initial design and planning through implementation, deployment, and production ownership.
Key Responsibilities:
Lead, mentor, and develop a team of Data Infrastructure engineers, fostering a culture of ownership, collaboration, and continuous improvement
Define and execute the technical roadmap for the organizations data infrastructure platform
Oversee the architecture, scalability, reliability, and performance of large-scale data systems and pipelines
Define and drive data quality standards, monitoring, and validation processes to ensure trust and reliability across the data platform
Partner with engineering and product teams to enable scalable data foundations for analytics, machine learning, and AI-driven initiatives
Lead cross-functional technical initiatives end-to-end, including requirements gathering, architecture design, implementation, deployment, and post-production ownership
Partner closely with cross-functional teams including Data Engineering, Analytics, Backend Engineering, DevOps, and Product Management
Drive operational excellence through monitoring, observability, automation, and incident management best practices
Ensure high availability and stability of critical production systems
Lead technical design discussions, architecture reviews, and engineering planning processes
Establish and promote engineering standards, development best practices, and quality assurance processes
Manage project prioritization, resource allocation, and timely delivery of strategic initiatives
Support recruitment, onboarding, performance management, and career development of team members
Evaluate emerging technologies and recommend improvements to the data platform ecosystem

You are the guardian of our source of truth. our company runs on a stack of 25+ interconnected SaaS tools, Salesforce, HubSpot, NetSuite, Workato, Gong, Outreach, IronClad, Okta, and more, and when that stack misfires, every team in the company feels it. Your job is to make sure it doesnt.
But ownership isnt just maintenance. As we scale our GenAI capabilities across the company, the quality of our core systems becomes the foundation everything else is built on. Youll be the one who ensures that when our GenAI Builder, our RevOps team, or our Finance team needs data, its clean, current, and accessible. Youre not a systems administrator. Youre the person who decides alongside with the business opener what the core stack looks like, how it grows, and how to build our agentic layer on top of it.
Youll manage a small team alongside a curated bench of specialized freelancers and subcontractors for deep technical work, and youll be the escalation point when things break. You report directly to the CFO.
What Youll Own
Core Stack Administration
Own the full tech stack: GTM (Salesforce, HubSpot, Outreach, Gong, ZoomInfo, Seismic), Finance (NetSuite, Stripe, Mesh, Opstream, Dokka, Expensify), Operations (JIRA, Notion, IronClad), and Infrastructure (Okta, Workato, Slack, Google Analytics) some of the tools will be co owned with IT
Ensure data integrity, system reliability, user access governance, and documentation across all platforms
Manage vendor relationships, license renewals, and cost optimization across the portfolio.

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 hiring an Engineering Manager to own and grow the data Science group - the R&D team behind 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 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.
 
 
 
the GenAI safety and security platform that keeps online experiences safe. We provide AI-driven detection, moderation, and red-teaming that protect billions of users across social platforms, marketplaces, gaming, and - increasingly - the GenAI applications reshaping the internet. Our data Science group builds the machine-learning and data systems at the core of that mission.

We're looking for an experienced hands-on Software Engineering Team Lead to lead a highly skilled team of backend and frontend engineers through implementation, delivery, iteration, and build scalable systems that serve our customers.

Responsibilities:
Foster a positive, collaborative culture and grow the teams capabilities.
Lead and mentor engineers to ensure on-time delivery, quality development, productivity, and efficiency by conducting and lead design reviews & code reviews.
Work together with product managers to translate requirements into scalable technical solutions.
Balance refactoring and evolution with steady delivery of new features.
Drive a culture of technical excellence, ownership, and continuous improvement.
Oversee system reliability, monitoring, performance optimization and incident response.

Were looking for a Director of Engineering Security to join our organization and lead multiple engineering teams building the next generation of secuirty products.
This is a hands-on engineering leadership role for someone who is a builder at heart, an experienced software engineering lead who loves to code, understands the full product and technical lifecycle, and knows how to scale both people and technology.
Youll work closely with the VP of AI and leaders across Product, Engineering, and other functions to turn ambitious ideas into high-quality products, while building and mentoring strong engineering teams.
What Youll Do:
Lead and manage multiple engineering teams, including managing and mentoring Team Leads.
Set the technical direction and execution standards across the teams.
Stay close to the technology and remain hands-on when needed- this is not a purely managerial role.
Drive the full engineering lifecycle, from architecture and design through development, deployment, and production.
Build and scale SaaS products in a fast-moving environment.
Partner closely with Product and other departments to translate business needs into technical execution.
Make pragmatic tradeoffs between long-term architecture and short-term delivery.
Encourage a culture of ownership, speed, experimentation, and continuous improvement.
Motivate engineers by connecting their work to the broader product and business goals.
Collaborate closely with managers and stakeholders across the organization.
Resolve conflicts effectively and build strong, collaborative relationships across teams.
Help identify technical risks and long-term implications while maintaining a strong focus on delivering results now.

We're looking for a Scrum Master to implement and refine Scrum methodologies across our R&D organization, keeping teams focused, synchronized, and empowered to deliver. This role sits at the intersection of process and delivery - going beyond facilitation to continuously improve ways of working and promote predictable, sustainable delivery.
What Youll Be Doing -
Scrum Implementation: Lead the continuous refinement of Agile ceremonies (Sprint Planning, Daily Stand-ups, Retrospectives) across multiple cross-functional teams.
Transparency & Delivery Management: Promote clear and transparent communication of progress, risks, blockers, and delivery forecasts. Work closely with Product and Engineering to ensure alignment and effective information flow across stakeholders.
Dependency Management: Coordinate across Mobile, Backend, FW, QA, and AI teams to manage cross-functional dependencies, ensuring smooth hand-offs and high-frequency release success.
Roadmap & Quarterly Planning: Support the creation and maintenance of high-level roadmaps aligned with quarterly planning commitments. Ensure alignment between technical execution and business objectives.
Jira Management: Own and evolve the Jira environment by designing efficient workflows, automations, and reporting capabilities that support scalable R&D operations.
AI & Automation: Identify and implement AI-driven solutions to reduce manual effort and optimize team efficiency.
Drive Operational Excellence: Define, track, and communicate KPIs to drive continuous improvement in productivity and efficiency.