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We are now extending our sensing capabilities into the defense and security domain, where robust, cost-effective perception is a decisive advantage for autonomous platforms, surveillance, situational awareness, and force protection.

The Software Tools Infrastructure team is a part of the Software group and acts as the focal point for cross-company tools, such as drivers, web services, visualization, simulation, image processing, data management, and data analysis tools. The team interacts with other teams in the company, including other R&D teams, Product and Operations groups, to provide cutting-edge solutions.

In this position you will:

Design, construct, and implement the customer-facing tools, including SW libraries (drivers) and UIs focusing on UX, including easy installation, documentation, and UI.
Interact with complex, multi-disciplinary systems

The Embedded Software team is responsible for developing multiple firmware and software packages that comprise our products. The team is responsible for the architecture and implementation of advanced elements, adhering to the quality standards of the automotive industry, within a highly complex and interdisciplinary system.

What you'll do

Design, implement and test real-time embedded software for multi-core ASIC devices
Meet the development standards of the Automotive industry for quality, safety and security
Interface with system/software architects, hardware designers, and system/test engineers

we are seeking an experienced EMC Engineer with the ability to understand complex systems to participate in the Qualification process for its revolutionary products.

What you'll do

Plan, coordinate, and perform EMC testing on full systems and components during the Design and Product Verification phase.
Influence hardware by recommending corrective actions at the PCB and system-level design, providing expert guidelines on grounding, shielding, filtering, etc.
Serve as a focal point in leading the analysis of EMC design requirements and findings at both the system and component levels
Based on collected data, determine if specifications, regulations, customers expectations, and acceptance criteria are satisfied - According to automotive and defense standards
Support the formation of technical reports, and be able to present conclusions to stakeholders

we are looking for a Simulation Engineer who will support our team's efforts to make the company succeed.

What you'll do

Perform thermal and CFD simulations of optomechanical assemblies using multiple FEA tools
Perform structural simulations of modal, PSD and shock
Analyze in-vehicle installation for both thermal and stiffness aspects
Hands-on thermal validation
Collaborate with multi-disciplinary R&D teams, including optics, system and HW

We are looking for a Python Software Engineer with 4-6 years of experience to join our ATE Software team, which is critical to the company. You will be developing software for advanced LiDAR calibration, characterization, and mass-production systems. This is a hands-on role working closely with other software, hardware, optics, mechanics, and system engineers.

What youll do:

Design, develop, and maintain complex software for LiDAR calibration and production-line automation
Develop algorithms, automation solutions, user interfaces, and software infrastructure for complex production systems
Analyze failures, improve processes, and continuously enhance code quality and development practices
Contribute to software architecture, system design, testing, and documentation
Collaborate closely with multidisciplinary teams to deliver reliable, mission-critical systems

We are looking for an outstanding System Qualification Technician with a strong ability to understand complex systems and take an active role in the qualification of revolutionary technologies.

Responsibilities:

Coordinate and execute hands-on functional and reliability test activities on full systems and components
Select, calibrate, and install appropriate instrumentation, including strain gauges, thermocouples, and accelerometers
Collect and analyze test data using data acquisition systems and software processing tools such as Python scripts
Evaluate test results to ensure compliance with specifications, regulations, customer expectations, and acceptance criteria in accordance with automotive standards
Generate formal technical reports and clearly present findings and conclusions to stakeholders
Conduct failure analysis investigations, diagnose failed components, and identify root causes
Perform testing activities that may require night shifts

We're looking for a hands-on Software Developer to join our R&D team, working on the full pipeline - cameras, video processing, automated production, graphics, and backend infrastructure. If you love low-level systems, real-time challenges, and seeing your code live in actual sports arenas, this is the role for you.

As part of your role, you will:
Develop and maintain high-performance C++ systems across the video pipeline.
Work on real-time video processing, ingest/transcode pipelines, and streaming infrastructure.
Collaborate with the team on backend services written in Python and Go.
Identify and resolve performance bottlenecks in multithreaded, low-latency systems.
Work closely with Product, QA, and DevOps to ship reliable, scalable features.
Leverage AI tools (primarily Claude) as part of your daily development workflow.

Required Software Developer
As a Software Developer, you will:
Be part of our security research team
Design, develop and maintain production-quality software, primarily in Python or similar languages
Translate research findings and prototypes into reliable, scalable and maintainable solutions
Build internal tools and infrastructure that enable and accelerate security research
Collaborate closely with researchers to understand technical domains and implement practical solutions
Own the software lifecycle from design and implementation through deployment and long-term maintenance
Investigate and resolve production issues, leveraging AI-assisted development tools where appropriate.

As the Head of AI Security, you will be the ultimate authority and strategic leader responsible for securing our AI/ML infrastructure, data pipelines, and deployed models, you will bridge the gap between advanced data science and enterprise-grade security. You will design, implement, and oversee security frameworks that protect our proprietary AI technologies, multi-agent systems, and RAG architectures.
Youll Own:
our companys end-to-end AI security strategy across AI/ML infrastructure, data pipelines, LLMs, RAG systems, and autonomous AI agents
Secure-by-design frameworks and security architecture for AI-powered products and platforms
AI threat modeling, adversarial testing, red teaming, and vulnerability management programs
AI governance, internal security policies, and alignment with emerging global AI regulations and standards
Security tooling, automation frameworks, and continuous monitoring capabilities for AI environments
Cross-functional security leadership across Data Science, AI Engineering, Product, Infrastructure, and SecOps teams
Youll Solve:
Protecting AI systems against emerging threats such as prompt injection, model inversion, data poisoning, and training data leakage
Preventing sensitive customer and enterprise data from leaking into training sets or model outputs
Securing complex AI architectures including LLMs, RAG pipelines, and multi-agent systems at scale
Embedding security seamlessly into the ML lifecycle without slowing innovation
Building scalable AI security operations through automation, monitoring, and continuous adversarial testing
Navigating evolving AI governance, compliance, and regulatory requirements across global markets
Youll Impact:
Maintain our companys reputation as a leader in secure and trustworthy enterprise AI
Build the foundation that allows AI innovation to scale safely and responsibly
Strengthen customer trust by protecting highly sensitive conversational and business data
Create resilient AI systems that can withstand real-world attacks and emerging threat vectors
Drive a security-first AI engineering culture across the organization
Shape the future of AI security, governance, and MLSecOps in a hypergrowth AI company.

As an Application Infrastructure Team Lead, youll spearhead the development of the core frameworks and services that power our entire ecosystem. In this role, youll sit at the vital intersection of application development and systems engineering, ensuring our platform remains resilient, high-performing, and developer-friendly as we scale.
If you are a technical heavyweight who loves Java but thrives on leading teams through complex data and infrastructure puzzles, this is your opportunity to build the foundation for our next phase of growth.
Youll Own:
Team leadership & mentorship: Guiding a high-performing engineering team and fostering a culture of ownership and excellence.
Core application infrastructure: Designing and maintaining mission-critical frameworks using Java and Spring Boot.
Technical standards: Defining and enforcing the benchmarks for code quality, system performance, and security across the entire stack.
Streaming & messaging pipelines: Owning the reliability and scalability of asynchronous communication using Kafka or SQS.
Youll Solve:
Data layer optimization: Leading specialists to tackle challenges in high availability and performance across PostgreSQL, MongoDB, OpenSearch, and Redis.
Distributed systems complexity: Designing robust pipelines for asynchronous communication and data streaming at scale.
Architecture gaps: Bridging the gap between DevOps and Product teams to align infrastructure capabilities with evolving business needs.
Youll Impact:
Engineering velocity: Providing the foundational building blocks that empower all product engineering teams to build faster and better.
System reliability: Ensuring the high availability, scalability, and security of mission-critical systems.
Technical culture: Driving a mindset of continuous improvement and technical excellence that resonates across the R&D 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.

As a Senior AI Infrastructure Engineer at our company, you'll lead the development and scaling of our machine learning training and AI infrastructure, enabling our AI and Research teams to build, train, and deploy cutting-edge AI solutions at scale. You'll collaborate across research, engineering, and business teams to create the foundations that power our companys AI innovation.
Youll Own:
Developing and evolving our companys machine learning platform, including shared libraries, development standards, CI/CD pipelines, and ML/AI tooling.
Designing and building scalable infrastructure that supports large-scale model training, experimentation with classic models and LLM, and validation.
Driving MLOps strategy and best practices, partnering with cross-functional teams to improve developer productivity, platform reliability, and operational efficiency.
Youll Solve:
Scaling machine learning infrastructure to support growing AI workloads, increasingly complex models, and rapid experimentation cycles.
Creating standardized, efficient workflows that enable research and engineering teams to move from experimentation to production faster and more reliably.
Youll Impact:
Accelerate AI innovation by building robust infrastructure that enables teams to develop, train, evaluate and validate models efficiently.
Improve the scalability, reliability, and consistency of machine learning development across our companys AI organization.

Were looking for an experienced and proactive Project Manager to join our growing team. In this role, you will take ownership of project setup, execution, and ongoing system maintenance, ensuring our clients receive seamless onboarding, reliable performance, and long-term value. You will lead cross-functional teams, balance multiple priorities, and drive project success through strong organization, communication, and problem-solving.

Responsibilities
Project Setup, Onboarding & Transition: Lead the project from kickoff through full implementation at the clients site. Ensure smooth transition, on-time delivery, and a high-quality onboarding experience. Coordinate with internal teams to guarantee readiness of resources, data, and tools.
Ongoing Stakeholder Communication: Act as the projects operational owner, managing setup of the system, client requests, system issues, and optimizations. Monitor system stability and performance to ensure long-term reliability and value. Drive improvements in workflows, resolving recurring bottlenecks and risks.
Cross-Functional & Stakeholder Management: Serve as the main point of contact for internal and external stakeholders (Customer Success, Support, Operations). Maintain transparency, responsiveness, and alignment across all project phases.
Issue & Risk Management: Proactively identify potential risks in the process, bottlenecks, recurring issues, or client dissatisfaction. Escalate appropriately and work cross-functionally to identify root causes.
KPI Tracking & Performance Monitoring: Define, track, and report on key performance indicators (KPIs) to measure project success and team performance. Use insights to drive accountability and continuous improvement.
Continuous Improvement: Conduct monthly result analyses, draw insights from experiences, and strive to achieve the Delivery department's goals. Analyze and optimize delivery workflows to improve efficiency and scalability.