דרושים » AI » AI Agent Engineer Solutions Architect

Responsibilities: Platform & Infrastructure
* Architect, build, and run the AWS/Kubernetes platform that hosts Alice's internal AI agents and tools; drive AWS Well-Architected pillars (operational excellence, security, reliability, performance, cost, sustainability).
* Own Infrastructure-as-Code: Terraform modules, standards, and reviews for Bedrock, agent runtimes, vector DBs, and supporting services. AI Systems
* Design and ship production-grade agents and multi-agent pipelines using the Anthropic Agent SDK, Claude Code, AWS Bedrock, and MCP - not wrapper frameworks.
* Own the full agent lifecycle: scoping prototyping eval deploy monitor iterate.
* Integrate agentic workflows into internal and product systems via APIs, databases, webhooks, Slack, and email. Reliability, Observability, Cost
* Build first-class observability across apps and infra: OpenTelemetry, Prometheus, plus LLM-specific tracing (Langfuse or equivalent), token/cost metrics, and eval pipelines.
* Define SLOs/SLIs and error budgets for AI services - latency, model fallback chains, eval regression gates, agent success rates. Lead incident readiness, response, and post-mortems.
* Drive FinOps: model routing by cost, cache hit rates, batch vs. realtime tradeoffs, budget alarms, per-team chargeback visibility.
* Implement guardrails: prompt-injection defenses, PII redaction, model allowlists, human-in-the-loop checkpoints, audit trails. Org Impact
* Identify high-leverage workflows across the organization and translate them into scalable agentic automations.
* Partner with R&D, Delivery, security, and external vendors to deliver platform capabilities.
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.

We are looking for a Senior Applied AI Researcher to design, evaluate, and deploy AI systems that operate over complex security data and workflows.
This role focuses on building reliable agent-based systems, developing semantic representations of security data, and enabling AI systems to reason across structured and unstructured sources. The work spans research, experimentation, and productionization.
You will work on problems such as relational discovery, schema alignment, semantic modeling, and graph-based retrieval, and turn promising approaches into real systems used by security teams.
What Youll Do
Design and build AI systems for security analysis and automation.
Develop methods for relational discovery, schema matching, and semantic modeling across heterogeneous security data.
Design and run evaluation and benchmarking frameworks for models, agents, and end-to-end systems.
Experiment with agent architectures, tools, and orchestration strategies.
Investigate system behavior, analyze failure modes, and improve system reliability.
Collaborate with engineering teams to bring research prototypes into production systems.

Were looking for a hands-on, entrepreneurial Team Lead to take full ownership of Ollys knowledge systems and build one of the most critical pillars of the product.
Responsibilities:
Technical and managerial leadership of the Knowledge team
Designing and building production-grade knowledge systems at scale
Making architectural decisions and tradeoffs
(LLMs vs embeddings vs heuristics, online vs offline computation, cost vs latency)
Driving research, experimentation, and innovation around what knowledge means for AI Agents
Hiring, interviewing, mentoring, and growing the team
Working closely with Agent, Platform, and Product teams

We are looking for a talented AI Algorithm Developer to join us in the research and development of our next-generation automatic sports video content engine. Our team operates at the intersection of Computer Vision, NLP, and Audio analysis. We dont just use models; we build multimodal pipelines that understand sports context like a human editor would.
If you are an expert in one of these domains (NLP, CV, or Speech) and are eager to master the others to build state-of-the-art Multimodal AI - we are looking for you!
What youll do:
Research and develop end-to-end real-time solutions for sports content automation using state-of-the-art Deep Learning (LLMs, VLMs, Audio models, and Generative AI).
Collaborate with Computer Vision and Audio experts to fuse different data signals into unified models.
Combine deep language models, Generative AI, and classical ML techniques to create high-quality solutions for demanding product-oriented tasks.
Manage the full R&D cycle: from problem definition and reading papers to implementation, prompt engineering, and productization with high autonomy.
Engage in collaboration with product and success teams to convert business goals into measurable algorithmic objectives.
Write robust, production-grade Python code that scales.

as an Agentic Pentest Director. Leading the development of agentic AI-driven penetration testing capabilities, focused on enabling autonomous security validation across modern software applications and infrastructure.

What Youll Be Doing

Become a company leader in the new product pillars that fall under your scope
Build a high-performing core engineering group by hiring top talent and fostering a culture of excellence, ownership, and collaboration
Drive the planning, execution, and delivery of key projects that impact the foundation of our product
Collaborate closely with product, architecture, security, product marketing, and other engineering teams to align technical vision and execution
Mentor and develop engineers, providing guidance and support for their growth
Help us continuously improve by bringing strategic thinking, hands-on leadership, and an agile mindset

We are seeking a driven, detail-focused professional to become a vital part of our team as a Generative AI Analyst. In this role, you'll dive into the cutting-edge of technology, meticulously analyzing various content infringements to secure the new wave of Generative AI tools. Your duties will include collaborating with experts in diverse fields such as Hate Speech, Misinformation, Intellectual Property and Copyright, Child Safety, among others.

Your tasks will involve writing adversarial; prompts to identify weaknesses in various AI models, including Large Language Models (LLMs), Text-to-Image, Text-to-Video, and beyond. You'll also oversee data management to guarantee the highest quality of outputs.

Responsibilities:
Developing adversarial and risky prompt strategies across several areas of abuse to expose potential vulnerabilities in models.
Managing projects end-to-end, from initial planning and oversight through quality assurance to final delivery.
Handling extensive datasets across multiple languages and areas of abuse, ensuring precision and meticulous attention to detail.
Ongoing investigation into new tactics for circumventing foundational models' safety measures.
Working alongside diverse teams, engineering, product, policy, to tackle new challenges and craft forward-thinking strategies and resolutions.
Promoting a culture of knowledge exchange and continual learning within the team.

The Staff Data & AI Architect will define and own the end-to-end architecture of our companys data and AI platform, spanning large-scale data systems, ML experimentation infrastructure, and production-grade model deployment. This role sets the architectural vision and technical standards for data and AI infrastructure across the company, ensuring scalable, compliant, research-accelerating systems that power both research and product development in a regulated biomedical environment.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Architect and evolve a scalable, resilient, and secure data and AI infrastructure supporting our companys research and product platforms. Identify recurring infrastructure and workflow challenges to drive the creation of generalized, reusable platform solutions.
Define scalable experimentation and MLOps patterns supporting experiment tracking, compute orchestration, dataset versioning, and reproducibility guarantees.
Lead the design and implementation of enterprise-grade data management. Establish and enforce data principles (e.g., FAIR, Medallion/Lakehouse architectures) to ensure data quality, lineage, discoverability, and reuse, while guaranteeing that all infrastructure meets security, privacy, and regulatory requirements.
Serve as the senior technical authority for data and AI infrastructure, partnering with Research, Engineering, and Product leadership to align architectural decisions with scientific and business priorities.
Lead technology evaluation and adoption decisions for AI infrastructure, balancing scalability, cost efficiency, compliance, and long-term maintainability.