דרושים » תוכנה » Senior Software Engineer

As a Senior Software Engineer on the Cortex Platform Application team, you will be a hands-on technical leader responsible for designing, building, and operating critical backend platform services used across Cortex. This role is for an engineer who can combine deep platform/backend expertise with strong ownership, practical execution, and cross-team influence. You will help build scalable and reliable services, guide technical decisions, improve engineering methods, mentor engineers, and raise the quality of how the team designs, ships, documents, tests, and operates its systems. The team owns a broad set of platform capabilities, including areas such as application configuration, dashboards and reporting infrastructure, metrics, multi-tenant and MSSP infrastructure, log forwarding, notifications, auditing, access and permission engines, filtering and querying infrastructure, and other shared application platform domains. We are looking for someone who is not only strong technically, but also enjoys joining a high-performing team, taking ownership from within, and helping turn strong execution into repeatable engineering practice. A successful candidate will quickly become a trusted part of the team by shipping meaningful work, learning the team's domains, and helping others move faster. Over time, this person will help the team increase delivery capacity while also improving how work is designed, documented, tested, operated, and shared across the organization. The right person will not act as an external advisor or abstract architect. They will join the team's day-to-day work, earn trust through execution, and help create organized technical influence from inside the team.
Key Responsibilities
Design, build, and operate scalable, reliable, and secure backend services for the Cortex Platform.
Act as a hands-on technical leader, writing and reviewing production code for critical platform services.
Lead technical design for complex backend and platform domains, balancing long-term architecture with practical delivery.
Own and improve core platform capabilities used by internal engineering teams and Cortex customers.
Drive operational excellence, including observability, monitoring, alerting, incident response, reliability, and participation in on-call.
Improve engineering methods around documentation, testing, design reviews, ownership models, and production readiness.
Mentor senior, mid-level, and junior engineers through design guidance, code reviews, production work, and day-to-day collaboration.
Collaborate closely with product managers, architects, security experts, QA, DevOps, and other engineering teams.
Help internal customers use platform capabilities correctly by creating clarity, alignment, and practical technical guidance.
Identify gaps in systems, processes, and ownership, and lead improvements without adding unnecessary process or friction.
Contribute to a calm, practical, low-ego engineering culture focused on ownership, execution, and continuous improvement.

We are looking for a Senior Full-Stack Engineer to build reliable, high-impact product experiences from browser to backend. You will own meaningful product areas, turn ambiguous customer problems into pragmatic technical solutions, and help set a high bar for quality, speed, and engineering judgment.

What youll do

Design, build, test, deploy, and operate end-to-end product capabilities.
Build polished frontend experiences with React and TypeScript.
Develop scalable backend services and APIs with Node.js and TypeScript.
Partner closely with Product and Design to shape solutions before implementation.
Make sound architecture decisions across application boundaries, APIs, data models, security, performance, and observability.
Use AI-assisted engineering tools thoughtfully to improve development speed and quality, while rigorously validating their output.
Build AI-enabled or agentic product capabilities where they create clear customer value.
Raise the engineering bar through code reviews, pairing, documentation, and mentorship.

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 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.

we are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.
What you'll be doing:

Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.

we are using technology to transform transportation around the world. From changing a single persons daily commute to reducing humanitys collective environmental footprint - weve got huge goals.
We are looking for an experienced Senior Software Engineer to join our team and help design, build, and scale the systems that power our products. In this role, you will work on high-impact projects that combine cutting-edge technology, complex distributed systems, and challenging algorithmic problems in transportation, routing, and navigation. You will have the opportunity to own features end-to-end, make key technical decisions, and shape the architecture and reliability of large-scale systems.
What Youll Do:
Architect, build, and scale robust, high-performance systems from initial design through deployment to production.
Own features end-to-end, from concept through development, testing, deployment, and maintenance, with strong accountability.
Develop features and APIs for concurrent applications in Golang.
Implement and improve geometric and graph algorithms to support core product
functionality.
Maintain Python and Java server applications, ensuring reliability and stability.
Write production-grade code that is efficient, reliable, maintainable, and optimized for performance.
Optimize application performance, uptime, and scalability, while maintaining high standards of code quality and thoughtful application design.
Run benchmarks and write analysis scripts for geographical data.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

Join our AI Platform group as an AI Engineer in the AI Core team and help build the next generation of AI-powered networking and security solutions at our company.
The AI Core team is responsible for developing AI applications, intelligent agents, and backend systems that integrate directly into our company products and workflows. As part of our companys strategic AI direction, the team focuses on turning modern GenAI capabilities into scalable production systems that help customers operate, troubleshoot, investigate, and manage complex networking and cybersecurity environments more effectively.
This role combines strong software engineering, modern GenAI technologies, and deep product impact. Youll work on building production-grade AI systems, integrating LLMs and agentic workflows into large-scale products, and helping shape how AI transforms cybersecurity and networking operations across the company.
We are looking for engineers who are excited about building real-world AI systems in production, not just experimenting with models, but designing scalable applications, integrating intelligent agents into complex products, and solving challenging engineering problems with direct customer impact.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop scalable APIs, services, and infrastructure supporting GenAI applications in production
Integrate LLMs, RAG pipelines, vector databases, and orchestration frameworks into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.

We're looking for a Senior Software Engineer, Infrastructure & Automation to join and play a key role in building the engineering infrastructure behind our AI-powered offensive security platform.

You'll design and build the infrastructure required to automatically validate and improve our platform and agents, including AI-powered agents for testing, evaluating, and automation of our systems that ensure our platform infrastructure and AI agents perform is reliable, repeatable, and effective at scale. Working closely with our AI Research, Security Research, and Engineering teams, among other things, you'll develop the infrastructure that enables rapid experimentation, deterministic validation, and continuous evaluation of autonomous AI attackers.

If you're excited about building developer platforms, testing infrastructure, and complex distributed systems in a fast-moving AI startup, we'd love to meet you.

Responsibilites
Design and build the testing and automation infrastructure that powers Tenzais platform and autonomous security agents. Define and shape the platform architecture for that goal.
Build deterministic and indeterministic validation tools for platform behavior and repeatable, data-driven evaluation for non-deterministic agent behavior.
Help develop continuous evaluation pipelines that measure performance, compare models and releases, detect regressions, and surface actionable results.
Build Python services and automation that orchestrate distributed test runs and manage their environments, inputs, and results.
Create internal tools and agents and CI/CD integrations that improve experimentation speed, developer productivity, and release confidence.
Partner with AI Research and Security Research to define evaluation methodologies, success criteria, and coverage.
Own systems end to end - from architecture and implementation through production reliability and continued evolution.
Contribute to technical design, architecture discussions, and code reviews across the engineering organization.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our company engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI at our company, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our companys internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our companys broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team at our company to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents at our company will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.