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Requirements:
Minimum Qualifications
5+ years of experience in SoC or IP verification
Advanced knowledge of SoC architecture/design, in-depth knowledge of verification flows and broad system view
Expected to have a deep understanding and shown experience in advanced verification processes, including coverage driven and formal methods
Extensive experience with SystemVerilog and UVM
Experience with verification infrastructure development
Knowledge of storage IPs and control oriented design - an advantage
Knowledge of formal, hardware acceleration - an advantage
Scripting and programming experience using several of the following: Perl, Python, Verilog, SystemVerilog, C, C++, and TCL
Preferred Qualifications
B.Sc / M.Sc in Electrical or Computer Engineering

Requirements:
What You Need for the Role
6+ years building and shipping production backend systems, including experience leading technical initiatives, processes and teams.
5+ years experience managing engineers, hiring, running 1:1s, giving feedback, and developing people, not just tech-leading.
Strong server-side engineering in at least two of: Node.js / JavaScript, Python, Java. Able to own a feature from data model to API.
Solid PostgreSQL - schema design, query writing and optimization, working with relational data at scale.
Proven experience designing and operating APIs (HTTP/REST/GraphQL) and a working command of auth and access control: OAuth 2.0, API keys, scopes, and RBAC.
Hands-on experience building LLM-powered features in production - direct work with LLM provider APIs (Anthropic, OpenAI, Gemini, Ollama or similar), function/tool calling, token optimization, structured outputs, and prompt engineering.
Experience with agentic systems: designing tool interfaces an LLM can use reliably, multi-step agent loops, and handling failure and recovery.
Working knowledge of MCP (Model Context Protocol) - or the depth in tool-calling and AI integration to ramp on it quickly - and a clear sense of what makes a tool definition easy for a model to use well.
Experience evaluating LLM systems: building eval suites, measuring tool-call and decision accuracy, and instrumenting AI behavior with tracing and observability.
A security mindset -treat prompt injection, untrusted inputs, least-privilege design, and data exposure as first-order concerns, not afterthoughts.
Comfortable in a small, fast-moving startup - high ownership, low hand-holding, and a willingness to build processes and infrastructure from scratch when needed.


Advantages
Retrieval and context engineering - RAG, embeddings, vector search, and semantic retrieval used to ground agents in API docs, schemas, and internal knowledge.
Experience running an MCP server, or a comparable AI-tooling integration, in production.
Cloud infrastructure (AWS / GCP / Azure), containers, and IaC.
Cybersecurity domain knowledge.
Open-source contributions to AI / agent tooling.

Requirements:
Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering in a leading University
4+ years of experience in software or test automation engineering
Proficiency with Python and Pytest
Experience testing embedded systems, firmware, or hardware-in-the-loop (HIL) setups
Experience building and maintaining CI/CD pipelines
Working knowledge of Git and Linux environments
Ability to quickly ramp up in new technical domains and adopt unfamiliar technologies
Preferred Qualifications
Experience building end-to-end test infrastructure for hardware/software automation projects
Strong failure analysis, troubleshooting, and system-level debugging skills
Experience with lab instruments (power supplies, oscilloscopes, etc.) and their automation APIs
Experience with MCUs (such as ESP32 or STM32) for building test fixtures and station controllers
Strong Bash scripting skills
Strong written communication skills, with the ability to turn a complex failure into a clear, reproducible bug report

Requirements:
B.Sc. in Mechanical Engineering or a closely related field.
At least 5 years of professional experience in mechanical design.
Strong 3D CAD (SolidWorks) skills and experience producing manufacturing-ready drawings.
Solid understanding of mechanical design fundamentals, including tolerances, fits, materials, mechanisms, and load paths.
Experience designing small, precise, tightly packaged mechanical assemblies.
Practical experience assembling, testing, troubleshooting, and improving physical prototypes.
Familiarity with machining, additive manufacturing, sheet metal, molding, and other relevant manufacturing processes.
Ability to work independently, make sound engineering decisions, and move quickly from concept to hardware.
Strong communication skills and the ability to work effectively across disciplines.
A proactive, curious, and highly hands-on approach.
Advantages:
Experience with robotic hands, grippers, prosthetics, medical devices, microsurgical instruments, or other miniature mechanisms.
Experience with tendon-driven or cable-driven mechanisms.
Knowledge of motors, gearboxes, encoders, force or tactile sensors, and electromechanical integration.
Experience with tolerance-stack analysis, FEA, mechanism simulation, or design optimization.
Experience designing products for reliability, assembly, and volume manufacturing.
Familiarity with testing mechanisms for lifetime, wear, friction, backlash, and repeatability.

Requirements:
What you bring
B.Sc. in Aerospace or Mechanical Engineering; M.Sc. with a structures or structural dynamics focus preferred.
5+ years designing and analyzing composite airframe or primary structure on aircraft, rotorcraft, UAS, or comparable flight vehicles.
Strong hands-on FEA capability in Nastran, ANSYS, or Abaqus across statics, buckling, and dynamics - with demonstrated correlation of models to physical test data.
Solid command of classical laminate theory, composite failure criteria, and the design of bolted and bonded joints in laminated structure.
Working fluency in structural dynamics: modal analysis, frequency response, and damping characterization, and an understanding of how these connect to radiated noise.
Experience carrying structure through physical test - static, fatigue, or modal/GVT - from test planning and instrumentation through post-test reporting.
Proficiency in Python or MATLAB for analysis automation, data reduction, and test-data processing.
Fluency in 3D CAD (CATIA, NX, or SolidWorks) and GD&T, with the ability to release production-ready structural definition.
Even better if:
Composite airframe experience on an eVTOL, UAM, or light aircraft program, especially during the prototype-to-flight-test phase.
Hands-on use of vibro-acoustic analysis tools such as Actran or VA One, or statistical energy analysis methods.
Exposure to composite structural substantiation under CS-23/Part 23 or rotorcraft rules, including familiarity with AC 20-107B practice.
A track record of owning structure at startup pace - from blank sheet to hardware on a test stand in months, not years.
Publications or graduate research in structural acoustics, damped composite design, or vibration transmission in built-up structures.

Requirements:
What you bring
B.Sc. or M.Sc. in aerospace, mechanical, electrical, or systems engineering, or equivalent demonstrated practice.
6+ years in systems engineering or integration on aircraft, UAV, spacecraft, or comparably complex electromechanical programs - including at least one carried from requirements through test.
Working command of ARP4754A development assurance and ARP4761 safety assessment - you have written FHAs and derived requirements, not just read about them.
Hands-on experience with requirements management tools such as DOORS, Jama, or Polarion, and a record of building traceability that survives external scrutiny.
Demonstrated ownership of interface control across mechanical, electrical, and software boundaries: ICDs, signal lists, connector-level definition, and disciplined change control.
Experience planning and executing ground or flight test campaigns - test plans, procedures, instrumentation requirements, and rigorous post-test reconciliation against requirements.
Enough fluency in structural dynamics, vibration, or acoustics to interrogate a noise requirement and recognize when a subsystem's verification evidence does not actually close it.
Clear written English - your requirements, interface documents, and verification reports are the program's backbone and, eventually, its certification record.
Even better if
Systems or integration experience on an eVTOL, UAM, or other novel VTOL aircraft program.
Direct exposure to certification with EASA, FAA, or military airworthiness authorities, including oversight of DO-178C/DO-254 software and hardware development.
Experience with MBSE methods and tools (SysML in Cameo or equivalent) for architecture and interface modeling.
Background integrating high-power electric systems, with the EMI/EMC and thermal discipline that comes with them.
Experience at an early-stage company where you wrote the first integration plan from a blank page and lived with its consequences.

Requirements:
What you bring
B.Sc. or M.Sc. in Electrical or Mechanical Engineering with a focus on electric machines, power electronics, or drives.
5+ years designing electric motors or motor drives for demanding applications - aerospace, automotive traction, robotics, or similar.
Deep working knowledge of electric machine noise mechanisms: torque ripple, cogging, radial force harmonics, and PWM sideband tones, and how to design them down.
Hands-on experience with field-oriented control and modulation schemes, including controller implementation and current-loop tuning in MATLAB/Simulink or PLECS.
Proficiency with electromagnetic FEA tools such as ANSYS Maxwell, Motor-CAD, or JMAG, including loss and force-harmonic prediction.
Demonstrated dyno or rig test experience: instrumentation selection, data acquisition setup, and debugging real hardware under load.
Strong Python or MATLAB skills for test data reduction, order analysis, and model correlation.
Comfortable owning hardware end to end - requirements through test - in a small team moving at startup pace.
Even better if:
Prior propulsion work on eVTOL, UAM, or other electric aircraft programs.
NVH background: order tracking, run-up/coast-down analysis, or experimental transfer path analysis.
SiC or GaN power stage design experience, including gate-drive and switching-loss trade studies.
Exposure to aerospace qualification and safety processes such as DO-160 environmental testing or high-voltage system safety standards.
Publications or patents in electric machine design, drive control, or electromagnetic noise reduction.

Requirements:
What you bring
B.Sc. in Aerospace or Mechanical Engineering; M.Sc. or Ph.D. with a focus on aerodynamics, fluid mechanics, or aeroacoustics strongly preferred.
5+ years of hands-on aerodynamic analysis and design experience on aircraft, rotorcraft, UAS, or wind energy systems.
Demonstrated depth in CFD for unsteady, separated, and interactional flows - including solver setup, meshing strategy, and turbulence modeling judgment - using tools such as STAR-CCM+, ANSYS Fluent, or OpenFOAM.
Working knowledge of aeroacoustic prediction methods (e.g., Ffowcs Williams-Hawkings integration, broadband source modeling) or proven ability to ramp quickly on them.
Experience planning or executing experimental aerodynamics campaigns - wind tunnel or flight test - including instrumentation selection and data reduction.
Strong scripting skills in Python or MATLAB for automation of simulation workflows, post-processing, and aero database generation.
Solid command of low-speed aerodynamic fundamentals: lifting-line and panel methods, boundary layer behavior, stall and separation physics, and propulsor-airframe interaction.
Ability to write clear technical reports and defend analysis assumptions in front of senior engineers; full professional proficiency in English.
Even better if:
Prior eVTOL, UAM, or rotorcraft experience, especially with hover-to-cruise transition aerodynamics.
Exposure to civil certification processes (EASA SC-VTOL, FAA Part 23/27 practices, or ARP4754A-structured development).
Peer-reviewed publications or conference papers in aeroacoustics, rotor aerodynamics, or unsteady CFD (AIAA, VFS, or equivalent).
Experience running large CFD workloads on HPC clusters, including job orchestration and cost-aware fidelity selection.
Track record at an early-stage hardware company - comfortable making defensible decisions with incomplete data on aggressive timelines.

Requirements:
What you bring
M.Sc. or Ph.D. in Aerospace Engineering, Electrical Engineering, or a closely related field, with a focus on dynamics and control.
7+ years designing control laws that flew - on crewed aircraft, UAVs, missiles, or other safety-critical dynamic platforms.
Deep command of classical and modern control: gain scheduling, robust control (H-infinity, mu-analysis), and nonlinear methods such as dynamic inversion or INDI.
Expert-level MATLAB/Simulink, including Simulink Coder or equivalent autocoding workflows, plus working Python or modern C++ for tooling and real-time code.
Hands-on experience carrying control laws through HIL testing into flight test, including telemetry-driven debugging and disciplined envelope expansion.
Solid grounding in flight dynamics, actuator and sensor modeling, and system identification from flight data.
Working knowledge of verification practices for flight-critical software in a DO-178C context, and the discipline to design for certifiability from the first commit.
Clear written English - your design documents, test cards, and analyses become the program's certification record.
Even better if:
Flight control experience on an eVTOL, UAM, or other novel VTOL aircraft program.
Exposure to ARP4754A/ARP4761 development processes or direct work with EASA/FAA certification teams; familiarity with SC-VTOL is a strong plus.
Enough aeroacoustics or psychoacoustics background to argue with the Acoustics team in their own language.
Experience standing up a GNC capability at an early-stage company, where you wrote the first version of everything.
Publications or patents in control allocation, trajectory optimization, or noise-optimal flight.

Requirements:
What you bring
M.Sc. or Ph.D. in aerospace or mechanical engineering, acoustics, or physics, with a focus on aeroacoustics or noise control.
4+ years of hands-on aeroacoustics work - rotorcraft, propellers, fans, turbomachinery, or airframe noise - in industry or applied research.
Proven experience running acoustic test campaigns: microphone arrays, beamforming, anechoic or wind tunnel measurements, and full calibration traceability.
Strong acoustic signal processing skills - spectral analysis, order tracking, de-Dopplerization, coherence-based source separation - implemented in Python or MATLAB.
Working command of source-noise prediction methods (Ffowcs Williams-Hawkings, semi-empirical broadband models such as BPM, or equivalent) and a clear-eyed view of their limits.
Fluency in community and certification noise metrics - EPNL, SEL, dBA - and the measurement procedures behind ICAO Annex 16 / 14 CFR Part 36 style testing.
Demonstrated ability to own a question end to end: from test plan to instrumented rig to a conclusion you would defend in front of the whole company.
Even better if
Prior acoustics work on eVTOL, UAM, or other advanced air mobility programs.
Exposure to noise certification campaigns or rulemaking discussions with EASA or FAA, including SC-VTOL context.
Background in psychoacoustics, sound-quality engineering, or jury testing methodology.
Publications in AIAA Aeroacoustics, JASA, or comparable peer-reviewed venues.
Experience standing up labs, rigs, and procedures from nothing at startup pace.

Requirements:
Software Development Experience: Hands-on experience as a Full-Stack or Backend Software Engineer, with strong proficiency in object-oriented programming, building complex business logic, APIs, and complex process automations.
AI-First Workflow: Demonstrated habit of using AI coding tools (Claude, Copilot, Cursor, or similar) as a core part of the daily development workflow, rather than an occasional resource.
AWS Familiarity: General familiarity with AWS services (S3, Lambda, and similar).
Mindset & Learning: Independent learner with the ability to adapt and understand concepts with agility; team player who thrives in a fast-moving, startup environment.
Communication: Strong written and verbal communication skills in Hebrew and English.
Salesforce Ecosystem: Previous experience developing on or working with the Salesforce platform (Apex, LWC, Visualforce, or complex Flows) - A strong advantage.