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

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.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless workers who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
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.

Required Senior AI Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the agentic AI platform that turns LLMs into reliable, production-grade capabilities. You care about clean APIs, well-defined service boundaries, and systems that teams can build on with confidence. We are AI-first across the board - every team builds and operates agents. You'll architect and ship the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation pipelines, tool-calling infrastructure, and retrieval systems. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments.
If you want to make a meaningful impact, join our mission and build the agentic AI platform that drives Sovereign AI products - this role is for you.
Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.

we are looking for a Senior Software Engineer to help build the core of our AI security platform and AI Control Plane.
You will build systems that help enterprises understand, monitor, and control how AI agents and LLM-based applications operate across their organization. We expect engineers to work in an AI-native way: leveraging and orchestrating AI agents to accelerate design, implementation, testing, debugging, and iteration, while owning the quality of the final result.
This role requires strong ownership, system design judgment, and the ability to turn complex AI-security problems into reliable production systems.
What you will do
Leverage and orchestrate AI agents and LLMs to design, build, test, debug, and ship core platform capabilities.
Build systems for monitoring, governing, and controlling AI agents, LLM applications, tool usage, prompts, context, policies, and runtime behavior.
Turn ambiguous AI-security problems into simple, scalable, production-grade systems.
Own technical decisions from design through production, working closely with Product, Security, and Engineering.

As an AI Engineer at our company, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive our company's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.
This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.
WHAT YOULL DO
End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.
Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.
Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.
Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.
Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.

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

What You'll Do
Lead a team of engineers building our company's core AI agent, from prompt architecture and tool orchestration to the real-time UI that makes the agent's thinking visible and actionable.
Own the full agent stack: working memory, dynamic persona infrastructure, context management, tool calling, and integration with backend AI services.
Drive architectural decisions around agent reliability, latency, and user trust, including how the agent reasons, when it asks for confirmation, and how users review and act on its suggestions.
Build and iterate on MCP integrations that extend what the agent can do, connecting it to publishing platforms, media tools, and external services.
Collaborate with Product and Design to shape the agent experience: making AI reasoning transparent, interactions natural, and outputs high-quality.
Champion engineering quality through observability (Langfuse), E2E testing, and CI/CD automation on prompts and agent behavior.
Grow your team members technically, help them navigate ambiguity (agent development is full of it), and maintain high velocity on a fast-moving roadmap.

Were looking for exceptional Senior Engineers who take full ownership of their work-from technical design through implementation and into real-world usage. This is a hands-on role for individuals who bring strong engineering fundamentals, curiosity across the stack, and a high standard for quality and reliability.
Youll join a team that values autonomy, deep thinking, and the ability to navigate both frontend and backend challenges. We expect engineers to care about how their systems behave in production-not just whether they compile-and to help build reliable, scalable software that stands up to real-world demands.
What Youll Do
Design, implement, and ship end-to-end features spanning web, mobile, backend, and infrastructure layers
Tutor, guide and help to nurture a culture of technical excellence throughout the development organization
Own your code through its lifecycle-from spec and architecture to deployment, monitoring, and evolution
Investigate and resolve issues that arise in staging or production, and help build tools that make doing so easier
Work closely with product and design to define technical solutions that deliver real user impact
Improve system architecture, performance, and development practices over time
Collaborate with peers through code reviews, design discussions, and shared ownership of technical quality

As a Senior Software Engineer on a search vertical, you'll help build systems that capture what is true about a domain. You'll work on extracting, connecting, retrieving, and reasoning over knowledge from the web and beyond, turning messy, real-world data into structured, trustworthy knowledge so AI agents can answer questions with precision and completeness.

You will optimize the retrieval and knowledge layer for a vertical: how a domain's content is indexed, linked into entities, ranked, and continuously refreshed, then measured and improved against rigorous IR metrics. This is an information-retrieval and systems role spanning indexing internals, hybrid retrieval, and entity resolution, with the goal of making each vertical the best place in the world to search its domain.

In this position, your responsibility will be to

Design, implement, and operate the retrieval system for a search vertical

Connect and tune the data pipeline, from ingestion to relevance tuning

Build knowledge-graph and entity-resolution layers: entity linking / NER, ontologies, and graph databases (Neo4j or similar)

Develop structured-extraction pipelines over messy, unstructured domain data

Reason about freshness and trust: model how confident we are in a fact and how stale it has become before we serve it

Define evaluation and quality metrics for relevance and drive measurable improvements

Collaborate with crawling, indexing, and ML teams to ensure retrieval and ranking requirements are met

Enable safe experimentation with retrieval, ranking, and extraction strategies

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.

We are seeking a Senior AI Engineer to join our AI team. This is a greenfield opportunity to shape how we build and deploy intelligent systems at Aura, designing LLM powered agents, building production AI infrastructure, and embedding agentic workflows into the engineering culture. The ideal candidate is a builder at heart: someone who ships fast, operates with urgency, and sees AI not just as a tool but as a platform for rethinking how software gets built.
What you'll be doing:
Build Autonomous Agents: Design and develop autonomous agents that accelerate Aura's engineering lifecycle - from AI powered grooming, to coding, testing and shipping to production. Reduce cycle time end to end.
Tackle complex engineering challenges: Contribute to the evolution of our AI capabilities. Build full-stack products and platforms that teams rely on for decision making.
Scale AI-Powered Operations: Build and scale AI driven tooling that reduces production downtime and cuts developer overhead in incident research and response.
Production AI Ownership: Own the full lifecycle of AI features - from prototype to production deployment, monitoring, and continuous iteration.
Evaluate \\& Improve: Build evaluation pipelines, observability tooling, and feedback loops to measure and improve AI system quality in production.
Cross-Functional Collaboration: Partner with Data Scientists, Product, and Engineering teams to identify high-value AI use cases and ship them end to end.