דרושים » תוכנה » Applied AI Scientist

We are looking for a talented AI Engineer to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.
What Youll Do:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Collaborate with engineering teams to design, build, and maintain production pipelines.

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

Were looking for a Senior Data Scientist to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

In this role, you will design, build, and productionize advanced models that help organizations secure AI systems across data, models, and runtime usage. Youll work closely with Product, Engineering, and Security teams to turn complex, real-world security problems into scalable, high-impact AI solutions.

This is a high-impact, hands-on role with true ownership, where your work directly shapes the intelligence powering a category-defining AI Security platform.


What Youll Do:

Own End-to-End Model Development (Research → Production)

Take full ownership of the model lifecycle: problem definition, research, prototyping, training, evaluation, deployment, and ongoing optimization.

Design and build scalable ML / AI solutions to detect, analyze, and mitigate AI-related security risks.

Ensure models are robust, explainable, and production-ready in real-world enterprise environments.

Partner Deeply with Product & Engineering

Collaborate closely with Product Managers to translate customer pain points and security requirements into clear modeling objectives.

Work hands-on with engineering to integrate models into production systems and data pipelines.

Balance research depth with pragmatic execution and business impact.

Build AI Security Intelligence

Develop capabilities across areas such as AI behavior analysis, anomaly detection, model governance, data risk detection, and usage observability.

Work with structured and unstructured data, including logs, prompts, model outputs, and metadata.

Continuously iterate on models based on usage patterns, feedback, and emerging threat vectors.

Lead Research POCs & Innovation

Stay at the forefront of LLMs, applied ML, and AI security techniques and bring new ideas into the product.

We're looking for an AI Engineer to join our team. As an AI Engineer, youll be a key member of our AI team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO
Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.

You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.

What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our company core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements
Design and oversee API strategies, event-driven architectures, and middleware patterns that support scalable AI feature delivery - including agentic workflows, intelligent data transformation, anomaly detection, and natural language interfaces layered onto ERP and CRM data
Collaborate with Engineering during build phases, conducting architecture reviews, providing hands-on guidance, and resolving complex technical blockers
Define non-functional requirements - latency, security, auditability, model drift monitoring - for AI components embedded in mission-critical business processes
Establish MLOps and LLMOps practices appropriate for our enterprise environment: model versioning, observability, and rollback procedures for production AI workloads