דרושים » תוכנה » Senior Software Architect, AI Products

Were looking for a hands-on AI Engineering Tech Lead to define and drive AI-native engineering practices, lead the architecture and development of scalable, intelligent systems, and embed AI across the software development lifecycle. This role involves providing technical leadership, identifying and solving architectural challenges, and collaborating cross-functionally to deliver high-impact, production-grade solutions.


Responsibilities:
Define and codify AI-native engineering practices, patterns, and guidelines to elevate the software development lifecycle.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Identify architectural risks, systemic bottlenecks, and long‑term scalability concerns - and proactively drive solutions.
Collaborate closely with Product, Customer success, Security and Business stakeholders to ensure technical solutions deliver real business impact.

We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within us as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

Were looking for an AI Software Engineer to own the RL Gym platform end-to-end: from architecting multi-site web environments that simulate real-world attack surfaces, to optimizing our in-house orchestration harness (AgenticVerse) for high-performance delivery into customer training pipelines.
This is a builder role. Youll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. Youll interact directly with customer engineering teams to understand their infrastructure constraints and deliver environments that meet their scale and reliability requirements.
Why this role
This is one of the few roles in the industry where your code directly influences how the next generation of AI models are trained. Youll be at the center of advancing AI safety, building systems that the worlds top labs depend on to make their models more robust. The work is technically deep, the problem space is genuinely novel, and the field is moving faster than any team can keep up with alone. Theres no playbook. Youll write it.
What youll do:
Platform & performance
Own and evolve AgenticVerse, our in-house orchestration harness that provisions and manages RL environments at scale. Focus on performance: low-latency provisioning, high concurrency, minimal overhead per environment instance
Design and build isolated, reproducible web environments using Firecracker microVMs or Docker containers
Architect multi-site scenarios (3-4 interconnected web applications per task) with rich interactions: drag-and-drop, file uploads, authentication flows, LLM-in-the-loop components
Implement deterministic verifiers that evaluate agent behavior with zero ambiguity
Customer delivery
Work directly with engineering teams at leading AI labs to integrate RL Gym environments into their training and evaluation pipelines
Translate customer specs into working environments, iterating rapidly on feedback
Own the technical relationship: SLAs, API contracts, integration architecture
Adapt environment delivery formats to cus tomer infrastructure (real-time API calls vs. offline batch, managed vs. raw artifacts)
Build customer-facing UIs when needed (dashboards, environment configuration portals, monitoring interfaces)
Rapid prototyping
Take ambiguous problem descriptions and produce working prototypes within days, not weeks
Validate new environment types, interaction patterns, and verifier approaches quickly
Build internal tooling that accelerates scenario authoring and testing.

We are looking for a Senior Software Engineer to join our small, core, professional development team in Tel Aviv. You will work closely with our CTO to create new software products that leverage our high-performance computational engine while modernizing our technical architecture.
This role is for an engineer who enjoys high-level systems work - taking our proven underlying tech and building the next generation of features and products on top of it. You will have a direct hand in shaping the architecture and integrating modern workflows into our ecosystem.
What you will do:
Product Creation: Lead the development of new, innovative software products, utilizing our robust computational foundation as a starting point for advanced capabilities.
Modern Architecture: Design and implement architectural improvements that allow us to integrate new features and AI-driven workflows efficiently.
Bridge the Stack: Interface our established, high-performance computational core with modern application layers and APIs.
Systems Design: Solve complex technical challenges by applying a systems-first mindset, ensuring our software remains clean, modular, and scalable.
High-Level Collaboration: Partner with our CTO and a small team of senior engineers to define our technical roadmap and uphold high standards of code quality.

Alice is a leading platform for Trust & Safety teams worldwide, combining cutting-edge AI with world-class expertise to protect users from the widest spectrum of online harms and keep customers two steps ahead of bad actors. We are looking for a Senior GenAI Data Scientist with strong hands-on experience in GenAI red teaming, adversarial testing, machine learning, and large-scale data analysis. You will develop the data science and ML capabilities behind an automated GenAI red-teaming platform. You will analyze and cluster adversarial prompts, identify emerging attack patterns, build models for automated prompt generation and mutation, and develop data-driven methods for prioritizing and evaluating security risks across different AI models. We are looking for a hands-on technologist with deep expertise in data science: clustering, scaling, machine learning, and statistical analysis. Key Responsibilities
* Build agents that act as data scientists at scale, reasoning, planning, and executing multi-step workflows to generate and analyze adversarial attacks.
* Manage and analyze prompt and response data from multiple sources (red-team campaigns, model evaluations, synthetic attacks); clean, curate, normalize, and label it for analysis.
* Analyze large volumes of structured and unstructured data to uncover trends, clusters, and anomalies, such as attack families, jailbreak techniques, and previously unseen patterns.
* Develop ML models and predictive algorithms to automate red-teaming.
* Build evaluation and monitoring pipelines to measure attack success and track model behavior across models and providers.
* Use statistical techniques and experiments to validate findings and ensure accuracy and reproducibility.
* Take research to production: build reliable, scalable systems optimized for cost and latency, with solid engineering practices (testing, CI/CD, telemetry).


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!

Alice is hiring a Senior Software Developer to lead the development of our internal malware research platform. This is a senior, hands-on role with end-to-end ownership of development and delivery. You'll be the technical authority — setting code-quality standards, making the architecture calls, and mentoring the developer team. What makes this role different is who you build for. Our users are our malware researchers, and they use the tool every day. Your job is to sit beside them, learn how they actually work, surface the heuristics and edge cases they carry in their heads, and build agentic tooling that compounds their productivity. The bar isn't "does it ship" — it's "do the researchers reach for it every day." Success is measured in researcher adoption and time saved, not features merged. Agentic workflows are core to how we build. You should be fluent using them and confident designing systems where agents run in production — with clear judgment about where an agent earns its keep versus where deterministic code or a human-in-the-loop is the right call. What You'll Do Lead development and delivery
* Own technical execution end-to-end: implementation, code review, and release.
* Translate research workflows and feature requests into well-scoped tasks with realistic, risk-aware estimates the team can plan against.
* Manage day-to-day execution: unblock people, sequence work, catch problems early.
* Set and defend the technical bar: review rigor, testing discipline, documentation, architectural consistency. Partner with the researchers — and amplify them
* Embed with malware researchers to understand their workflow and capture the tacit knowledge and edge cases no spec ever wrote down.
* Translate that knowledge into reliable agentic tooling — and know when an agent is confidently wrong before it ever reaches a researcher.
* Spend roughly 5–10% of your time doing actual malware research (with structured onboarding) to stay close to how the tool is used.
* Be willing to tell a researcher when a proposed workflow won't automate well — and explain why. Be the technical authority and mentor
* Make the hard architecture and design trade-off calls.
* Mentor through code review, pairing, and design discussions. Raise the level of everyone around you.
* Dive deep on the critical, difficult features and bug fixes yourself.
* Design agentic workflows into the architecture from the start, and build the evaluations and guardrails that keep them trustworthy.

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!

We are looking for an exceptionally strong software engineer to join our Technology organization. You will be part of a business-facing team responsible for building and evolving the core systems that power our Quant strategies. This is an AI-forward team: large language models (LLMs) and AI agents are part of our daily workflow - from writing and reviewing code, to automating operational toil, to building internal copilots and agentic tools that the whole team relies on. You won't just use AI to move faster; you'll help shape how it's applied across our engineering practice.

Design and build data pipelines and the data layer.
Develop and maintain the computational frameworks and infrastructure that run our quantitative strategies at scale.
Implement and enhance quant-related software systems for data, research, portfolio construction, and trading.
Work closely with Researchers, and Quants as a hands-on engineering partner, helping them turn ideas into robust production solutions.
Gain exposure to the full lifecycle of the systematic/quant business, from data ingestion through research, implementation.
Build and integrate AI-powered tooling - LLM agents, copilots, and automation - into engineering and research workflows.
Use AI coding assistants and agentic developer tools to ship higher-quality software faster.

We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.
If you've built agents that actually made it to production - and you care as much about evaluation, guardrails, and reliability as you do about capability - we want to talk to you.
Responsibilities
Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
Optimize agents for latency, cost, and reliability at enterprise scale.
Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

Were looking for a Founding AI Engineer to build and define the research function at Upriver from zero. This is a rare opportunity to work on some of the hardest unsolved problems in applied AI and agents, with massive ownership, visibility, and room to grow into leadership quickly.

What Youll Do
Lead the AI domain at Upriver: Take ownership of our agent architecture and help define its next phases, standards, and direction.
Solve hard, unsolved problems: Work on challenges in AI agents, reasoning over complex systems, and autonomous decision-making that dont yet have clear playbooks.
Build production AI: Design, implement, evaluate, and deploy AI systems used by real customers.
Be outward-facing: Publish technical blogs, benchmarks, and papers; represent Upriver in the AI and data community.
Move fast with autonomy: Own problems end-to-end with minimal guidance, working directly with founders.
Deliver real customer value end-to-end: take features from idea to production, see them used by customers, and iterate based on real-world impact.

we are looking for a Senior Data Analyst.
The Custom Feeds team turns Placer's data into production-grade bespoke data products for our largest customers - tailored to specific business questions and shipped on a recurring basis. We're looking for a Senior Data Analyst who is both a pipeline builder and a data researcher. You'll own custom recurring feeds end to end - from methodology for new metrics, through pipeline design, to final acceptance before delivery. You'll lead conversations with internal stakeholders (US-based customer-facing teams and colleagues across R&D) and help generalize recurring logic into reusable models, metrics and packages the whole team builds on. Ideal for a rigorous, independent thinker looking for a delivery-oriented role where impact is tangible.
Responsibilities:
Own custom feeds from requirements through delivery and ongoing maintenance
Develop methodologies and acceptance criteria for new metrics
Build reproducible, tested production pipelines in PySpark on Databricks, orchestrated with Airflow and Terraform
Partner with Solution Engineers and customer-facing teams on timelines, methodology and customer feedback
Build reusable components and packages; collaborate with R&D and Data Science to reuse existing datasets, models and products - and make your work reusable by others