דרושים » תוכנה » Senior Software Engineer, Vertical Search (Agentic Search)

We are looking for a Senior AI Software Engineer to build the agents that sit on top of our search platform: systems that take a user's intent, break it into steps, gather and verify information from the web, and return answers an agent can act on. You will work across applied research and engineering, designing how agents plan, call tools, retrieve, and reason so they accomplish open-ended tasks reliably and at scale.

This is a high-ownership role at the intersection of agent systems, retrieval, and product. You will turn frontier-model capabilities into dependable, production-grade agent behavior, and you will own that behavior end to end, from the prompts and tools to the evaluation that proves it works.

In this position, your responsibility will be to

Design and build AI agents that plan, retrieve, and reason over real-world information to complete open-ended tasks

Build the tool interfaces and context engineering that let frontier models use our search and other tools effectively

Mine and analyze usage data to build agents that learn and improve continually from how they are used

Turn new model capabilities into reliable product features, and own them from prototype to production

Define the evaluations, metrics, and guardrails that prove an agent is accurate, grounded, and safe

Improve agent quality across reasoning, planning, tool use, and grounding against real user tasks

Build the backend and infrastructure that run agents reliably under high volume

Collaborate with the search, ML, and product teams to make agent and platform capabilities reinforce each other

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.

As a Software Engineer - Scraping Specialist, youll build the systems that power how AI interacts with the live web. Youll design and implement large-scale, intelligent web acquisition pipelines, making sense of an ever-changing online ecosystem and transforming it into structured, high-quality data.

This role blends technical understanding of browsers, networks, and automation with hands-on engineering. Youll work on adaptive systems that navigate modern websites, understand evolving web interaction ,detection systems, and gather meaningful information safely, efficiently, and at scale.

Your work will directly shape ability to provide AI agents with accurate, real-time knowledge of the world , bridging the gap between the open web and intelligent reasoning.

What Youll Do
Build distributed data acquisition systems that capture and structure the live web
Investigate and analyze browser internals, fingerprinting, and anti-automation systems to develop stealthy, adaptive orchestration layers
Prototype and deploy intelligent automation frameworks using Playwright, Puppeteer, and low-level browser control protocols (CDP)
Conduct hands-on research into network flows, JavaScript-based protections, and emerging web standards affecting automation
Collaborate with AI and infrastructure teams to integrate real-time web data into retrieval pipelines and LLM-powered agents
Translate deep technical insights into production-grade components, balancing research freedom with engineering rigor
Continuously evolve capabilities in resilience, speed, and authenticity of web interaction

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

We're looking for a Software Engineer to join our core engineering team and help build the infrastructure behind one of the fastest-growing AI APIs. You'll work on systems that handle massive scale across a distributed microservices architecture running on AWS. You'll ship fast, take ownership of critical systems, and solve hard infrastructure problems as we grow.

This is a great role for an engineer who loves building ambitious systems from scratch, and wants to tackle the kind of scale and complexity challenges typically reserved for much larger companies.

What Youll Do

Design and build high-performance distributed systems

Design and implement backend infrastructure and API endpoints

Build and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors

Improve performance, monitoring, and reliability across the stack

Own core systems and contribute to key architectural decisions

Help shape a strong engineering culture focused on velocity and quality

we are looking for a Senior Software Engineer to join a strong and dynamic AI Engineering team. We are the focal point for AI initiatives , striving to constantly bring innovation and leverage AI capabilities across all company teams and products.

Today, AI is central to how operates, across the entire organization. It allows us to move fast and release features at a rapid pace, empowers non-technical to utilize AI tools for increased efficiency, and provides the backdrop for much of the innovation currently occurring in the company.

If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints - consider applying for this position.
What you will be doing:

Design, build, and maintain reusable AI capabilities - including models, tools, APIs, and platforms that power both internal and customer-facing solutions.
Develop and maintain our internal MCP server that easily and securely exposes vast data stores to AI agents.
Create and implement robust evaluation frameworks and AI guardrails to safeguard value and ensure model reliability.
Establish deep expertise and sustainable AI engineering practices.
Promote AI readiness and track adoption across the company to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Take full ownership of projects: from gathering requirements from non-technical internal users to development, deployment, and operation.
Act as a consultant and advocate for AI engineering, helping other teams leverage the platforms and tools you build.
Partner with teams across to accelerate AI adoption and productization efforts.

In this role, you will act as the primary architect of the "nervous system" that bridges the gap between sophisticated AI models and real-world business logic. You will design and maintain the critical infrastructure that enables intelligent, autonomous features to function reliably at scale, moving beyond simple API wrappers to build deeply integrated AI systems. You will take ownership of the entire data flow, where you will develop high-performance RAG (Retrieval-Augmented Generation) pipelines and complex agentic workflows that provide users with accurate, context-aware responses.
Your Impact
Champion system stability by implementing rigorous evaluation and monitoring frameworks, ensuring that as our AI capabilities grow, our production environment remains fast, cost-effective, and secure.
Ultimately, you will be the technical force that transforms cutting-edge AI research into stable, scalable products that define the future of our platform.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

We build Agentic Network Security Orchestration, a platform where autonomous AI agents reason over a live network, make decisions, and act. Our group sits at the center of our company's AI strategy. We turn some of the best cyber security data in the world into agents that keep enterprise networks understood, secured, and in control.
You'll own some of the platform's hardest problems:
Network reasoning and connectivity analysis - model a customer's live network as a knowledge graph of topology, routing, gateways, and policy. Answer what humans struggle to: can this reach that, and exactly which path does it take? This is the engine behind autonomous troubleshooting.
Structure at scale - find patterns in massive, messy networks. Group objects, traffic, and access patterns so agents can reason about intent, not one rule at a time.
Real networks. Real scale. Real impact on how enterprises secure their infrastructure.
What you'll do
Design and build the services that model, reason over, and answer questions about live enterprise networks
Turn network topology, routing, and firewall policy into a knowledge graph agents can navigate
Build clustering and analysis that find structure across millions of connections
Design scalable, reliable data pipelines and APIs that process network traffic at enterprise scale
Partner with data scientists to take models and agents from research into production
Own hard problems end to end - from a vague question to a system in customers' hands.

We are looking for a Senior Data Engineer with a strong Backend Engineering background to architect the intelligent data foundation.

This is not a traditional ETL role. You will build the critical infrastructure that feeds our Agentic Growth Engine, enabling AI agents to perceive the market, make decisions, and drive growth. You will own the semantic layer, design the agentic data architecture (both data retrieval and training infrastructure), and build sophisticated extraction processes that allow our system to "read" the competitive landscape.

What you'll do
Architect the Agentic Data Infrastructure: Design and maintain the core data pipelines and storage systems (GCP/BigQuery/Postgres) that power our AI agents, ensuring high availability and low latency for decision-making.
Build the RAG & ML Backbone: manage the infrastructure for training data, vector search, and regression testing. You will ensure our agents have access to clean, context-aware data for RAG workflows.
Develop Agentic Extraction Processes: Build complex, resilient data extraction systems (crawlers/scrapers) to map competitive landscapes and product trends, feeding raw market data into our analysis engine.
Own the ELT & Semantic Layer: Manage the transformation of raw data into a consistent, business-ready semantic layer that serves as the "source of truth" for both analytics and AI models.
Run Predictive Models: Operationalize and deploy predictive models on top of our data, integrating them into the core product workflow.Define Data Standards: As a senior owner, you will establish the data engineering best practices, coding standards, and architectural patterns that the rest of the engineering team will follow.