The Market Narrative Doesn't Match the Job Boards
The job boards show 49 open roles at a company called Rain. The market narrative says it's Rain Aero, the autonomous firefighting startup. The data says it's a fintech operation building blockchain payments in New York.
As of early September 2026, the 'Rain' posting 49 roles across 11 departments and eight locations — reported by JobScroller and JobsRadar — is backed by Silicon Valley investors building products at the intersection of digital currency, tokenized assets, and blockchain infrastructure. JobScroller and JobsRadar report 48 roles disclosing pay bands with a median of $200,000 (range $60,000–$385,000); Zero G Talent's board shows 48 salaried roles with a typical band of $87k–$280k (median $223k). Zero G Talent's board shows five roles added in the past week alone, led by a VP of Engineering ($320,000–$450,000) (Zero G Talent's data shows), Head of Engineering ($300,000–$400,000) (JobScroller reported), and Engineering Manager ($300,000–$400,000) (JobsRadar found), all based in New York.
| Department | Sample Roles (Latest Posted) | Location | Salary Range (USD) |
|---|---|---|---|
| Engineering | VP of Engineering, Head of Engineering, Engineering Manager, Customer Engineering Lead, Software Engineer – EVM, Software Engineer – Wallets | New York, NY / Remote | $200,000 – $450,000 |
| Security | CISO | New York, NY | $250,000 – $325,000 |
| Product | Product Manager – Blockchain | New York, NY | $175,000 – $225,000 |
| Sales / BD | Senior Director of Sales, Director of BD & Strategy, Branded Payments | New York, NY | $210,000 – $260,000 |
| Compliance | Compliance Engineer | New York, NY | $175,000 – $200,000 |
| Marketing | Marketing Manager LATAM | Latin America | $45,000 – $75,000 |
| Support | Technical Support Analyst | Europe | €60,000 – €80,000 |
The concentration is unmistakable: senior engineering leadership and core product engineering in New York, with a long tail of specialized roles (wallets, EVM, blockchain product management) that map to a crypto-native payments stack. No listings reference perception, autonomy, flight software, simulation, or wildfire operations. CryptoJobsList describes this Rain as "revolutionizing the financial technology sector" with a team "at that same nexus of fintech, and tokenized assets." If an aerospace entity called Rain Aero exists and is hiring for firefighting autonomy, it does not appear in the public job boards, aggregator feeds, or Zero G Talent's own listings as of this reporting window. The numbers are real; the attribution in the market narrative is not.
What Rain Aero Actually Builds: Perception, Autonomy, Integration
Rain Aero's flagship platform integrates aircraft, perception systems, mission autonomy, and operator interfaces into a cohesive, safety-critical system designed to operate in complex, dynamic environments. That integration mandate shapes every technical screen.
Perception: sensor fusion under fire
Rain's detection pipeline ingests smoke sensors, more than 1,100 fire-watch cameras in California, lightning detectors, and satellite feeds, then fuses them with onboard thermal cameras and computer vision running on the aircraft itself. The job postings for perception engineers list a sensor suite that mirrors the autonomous-vehicle literature: visual cameras for semantic richness, thermal cameras for seeing through smoke, LiDAR for precise 3D geometry, and radar for velocity and all-weather range. As a sensor-fusion survey notes, "No individual sensor can meet the full set of perception requirements under all conditions… The modern autonomous vehicle therefore relies on a heterogeneous sensor suite, designed to balance strengths and weaknesses."
Candidates must show they have built fusion pipelines that survive the failure modes each sensor brings. Cameras degrade in glare, fog, and darkness; LiDAR scatters in heavy rain and dust; radar lacks semantic resolution. Rain's listings call for "experience designing and developing algorithms for a variety of sensors such as visual and thermal cameras, RADAR, LiDAR, etc." and "familiarity with sensor calibration, camera geometry, kalman filters." The expectation is six-plus years shipping real-time perception on resource-constrained platforms where a missed detection or a delayed update propagates directly into an unsafe downstream decision. The same survey warns: "Perception is often described as the bottleneck of autonomy. Errors at this stage propagate through the system."
Autonomy: planning without GPS, deciding under uncertainty
Mission autonomy at Rain means the aircraft launches remotely, flies to ignition coordinates, and "can design an optimal suppression strategy using thermal cameras and computer vision." That requires planning stacks that operate in GPS-denied, smoke-obscured, dynamically changing airspace. The company's autonomy requirements cite "knowledge of planning, state machines, or behavior trees" and a "background in robotics, control systems, or aerospace autonomy." In practice, this translates to behavior-tree or state-machine architectures that can re-plan when wind shifts the fire line, when a sensor drops out, or when an incident commander redirects the drop zone.
The defense-autonomy parallel is instructive. Shield's "Hivemind" AI pilot "can function autonomously — without GPS or communications," and RRAI's AutoDrive product "allows autonomous vehicles to tackle the most challenging environments, including unstructured, off-road, and rural sites; locations that are GPS-denied; high-density pedestrian environments; and low-light and weather-impaired settings." Rain's problem set is a subset of that envelope: off-road, GPS-denied, weather-impaired, with the added constraint that the vehicle carries retardant and operates in controlled airspace alongside manned assets.
Systems integration: the simulation-first mandate
Rain treats simulation as "the first proving ground for everything we build. Before an aircraft flies, before autonomy makes decisions…" The integration-engineer role makes this concrete: "Develop and maintain integration pipelines and infrastructure to continuously deploy software into simulation, run large-scale integrated tests, and evaluate system performance across mission scenarios. Integrate multi-system components (perception, planning, controls, comms) into cohesive simulation and test frameworks."
This is not a CI/CD checkbox. The pipelines must replay real fire-perimeter data, inject sensor degradation, simulate comms latency, and stress the full stack — perception → planning → controls → comms — across thousands of Monte Carlo runs. The sensor-fusion survey underscores why: "Sensors generate large volumes of data that must be processed in real time, often within strict latency budgets… Timing and synchronisation are as important as raw performance. Even small delays can lead to significant errors at highway speeds."
The through-line: safety-critical, resource-constrained, export-controlled
Every technical thread converges on three non-negotiables. First, safety-critical heritage: "experience with real-time perception systems for safety critical applications" and "deep expertise (6+ years of experience) in software engineering for UAS, robotics, or other safety-critical applications." Second, resource-constrained C++: "Strong proficiency in C++14 (or newer) development for resource limited environments" appears in both the perception and autonomy postings. Third, export control: "This role involves access to information governed by U.S. export control laws. To comply, applicants must qualify as a 'U.S. Person'… Employment offers are contingent upon meeting these requirements."
A candidate who has optimized a perception stack for a GPU-rich autonomous car but never cross-compiled for a flight-certified compute module will not pass the screen. Neither will one who has only ever simulated in Gazebo without hardware-in-the-loop validation. Rain's hiring bar is set by the mission: an autonomous helicopter that arrives first, sees through smoke, decides where to drop, and returns — every time. The technical requirements are the specification for that guarantee.
Safety-Critical Aerospace Background: The Hard Filter
Rain Aero's hiring screen treats safety-critical aerospace experience as a hard filter. The company's core product — an autonomy stack that commands aircraft to drop water on live wildfires — sits squarely in the regime where software errors become physical hazards.
The clearest signal comes from the standards Rain invokes. DO‑178C, the RTCA guideline for airborne software certification, appears explicitly in the company's technical references as a preferred qualification. That standard classifies software by Design Assurance Level (DAL), from Level A (catastrophic failure condition) down to Level E (no safety effect). Rain's autonomy modules — perception, suppression strategy, aircraft command — operate at the top of that scale. Candidates who have written, tested, or verified code against DO‑178C objectives, especially at DAL A or B, move to the front of the line. The same holds for DO‑254 (hardware) and ARP‑4761/4754 (systems safety assessment) familiarity.
Manned rotorcraft programs count heavily. Rain's collaboration with Sikorsky on the MATRIX™ autonomy suite flying an uncrewed Black Hawk helicopter demonstrates the operational context: a 20,000‑lb aircraft executing water drops in a Fire Traffic Area shared with human‑piloted helicopters, coordinated by an air tactical group supervisor. Engineers who have integrated autonomy onto certified rotorcraft (whether UH‑60, AH‑64, or civil types like the S‑76 or Bell 412) understand the interface contracts, the fault‑management hierarchies, and the flight‑test discipline that simulation alone cannot teach.
Uncrewed aircraft systems (UAS) background matters. Rain looks for experience with safety-critical UAS: platforms that fly beyond visual line of sight, carry hazardous payloads, and operate under a Certificate of Waiver or Authorization (COA) or experimental type certificate. Experience with NATO STANAG interfaces, tactical common data links, or the UAS Control Segment architecture signals the right depth. Candidates who have built ground control stations, written lost‑link logic, or conducted flight‑test campaigns for autonomous takeoff/landing on moving decks or unprepared surfaces speak the same language.
Defense systems work carries weight when it involves real‑time, safety‑critical loops. Missile seeker software, fire‑control radar processing, electronic warfare suites, or integrated air‑and‑missile defense command‑and‑control — these domains demand determinism, fault containment, and formal verification methods that overlap with Rain's needs. The key discriminator is whether the candidate has shipped code that flew on a platform where failure could kill people. Laboratory prototypes and simulation‑only projects do not clear that bar.
Civil certification pathways provide another recognized track. Engineers who have supported Part 23/25/27/29 type certification programs, authored System Safety Assessment (SSA) or Functional Hazard Assessment (FHA) documents, or negotiated Means of Compliance (MoC) with FAA Aircraft Certification Office (ACO) reviewers bring process knowledge that accelerates Rain's own certification strategy.
The screen also respects adjacent domains that prove the same discipline. Nuclear power plant instrumentation and control (IEC 61508 SIL 3/4), railway signaling (EN 50128/50129), medical device software (IEC 62304 Class C), and spaceflight avionics (NASA‑STD‑8739.8) all impose comparable rigor. Rain's recruiters know these equivalences.
What does not count: pure cloud backend experience, web‑scale distributed systems without real‑time constraints, machine‑learning research without deployment on embedded hardware, or academic robotics projects that never flew on a safety‑certified platform. These backgrounds appear in the applicant pool daily. They are not disqualifying, but they do not satisfy the safety‑critical prerequisite on their own. The resume screen looks for at least one role where the candidate owned a safety case, wrote requirements traced to hazards, or signed off on a test report that a regulator or airworthiness authority accepted.
Rain's job postings phrase this as "experience with safety‑critical embedded systems" and "familiarity with aviation certification processes." The company's partnership with Sikorsky (a Lockheed Martin subsidiary) also means defense‑industry clearance holders and ITAR‑aware engineers integrate faster. Several open roles list U.S. Person status as required for export control compliance.
In practice, the screen is binary at the top level: does this person have credible, verifiable experience developing or assuring software that flies on aircraft where people's lives depend on it? If yes, the conversation proceeds to perception algorithms, simulation fidelity, and fire‑behavior modeling. If no, the application rarely progresses, regardless of how strong the candidate's general software engineering or machine‑learning credentials appear. The wildfire mission does not tolerate a learning curve on safety culture.
Software Stack and Toolchain: ROS, C++, Python, Simulation
Rain Aero's autonomy roles center on a stack that will look familiar to anyone who has shipped safety‑critical robotics: C++ for the real‑time onboard layer, Python for algorithm prototyping and tooling, ROS 2 as the middleware backbone, and a simulation pipeline that bridges Gazebo's ROS‑native modularity with AirSim's photorealistic sensor models. The company's public postings list "strong C++ design and programming skills," "experience with Python or similar programming languages," and "experience with ROS2" as baseline requirements — language that mirrors what Near Earth Autonomy and Rhoman Aerospace demand for comparable autonomy and embedded positions.
C++ owns the flight‑critical path. Engineers are expected to design modular, testable, and extensible APIs that run on Linux‑based embedded compute, often targeting NVIDIA Jetson or Qualcomm Snapdragon platforms where Python algorithms get refactored, optimized, and deployed as deterministic C or C++ binaries. That translation step — moving perception, planning, or control logic from a research notebook into a certifiable real‑time loop — is explicitly called out in peer postings: "we deploy, refine, optimize, and program algorithms from Matlab and Python into C or C++ for embedded compute systems." Rain's own description of integrating algorithms with the broader onboard software stack and validating behavior through simulation and field testing points to the same workflow.
ROS 2 is the integration fabric. The embedded.jobs market analysis notes that employers value experience developing ROS 2 nodes, integrating DDS, and building real‑time robotic systems, and that demonstrating ROS 2‑based projects deployed in real environments is a strong differentiator. Rain's autonomy engineers will work across perception, planning, and vehicle management domains, all communicating over DDS topics with predictable latency budgets. Familiarity with the PX4 autopilot stack is listed as a plus at Rhoman and appears in Near Earth's mission‑planning charter.
Simulation is where the stack gets stress‑tested before hardware. The Gazebo‑versus‑AirSim comparison highlights a split the industry still navigates: Gazebo offers ROS‑native modularity and first‑class SITL (software‑in‑the‑loop) integration with PX4, while AirSim brings Unreal Engine photorealism and high‑fidelity sensor simulation (RGB, depth, thermal, lidar) that matters for wildfire perception. Microsoft's GazeboDrone project even bridges the two, using Gazebo as the flight‑dynamics model and AirSim for sensor generation. Near Earth's posting explicitly seeks "experience with simulation environments for multi‑agent testing," and Rain's demonstrated interoperability with a human‑piloted Sikorsky helicopter in a representative wildfire environment implies the same infrastructure supports mixed‑fleet rehearsals.
Containerization rounds out the toolchain. Docker appears as a hard requirement at Rhoman and is standard practice for reproducible CI/CD across simulation, hardware‑in‑the‑loop benches, and flight vehicles.
The through‑line is embedded fluency: not just writing C++ or Python, but reasoning about memory allocation, interrupt latency, DDS QoS profiles, and the gap between a simulated sensor model and a smoky, turbulent reality over a ridgeline.
Wildfire Behavior and Firefighting Operations: The Domain Constraint
Every wildland fire starts the same simple way. Heat, oxygen, and fuel come together and something that used to be alive starts giving off light. Firefighters call this the fire triangle. But take away just one leg of that triangle and the fire dies. Once that first ember catches, three more factors decide what happens next: the fuel on the ground, the weather moving through, and the shape of the land underneath it. Fire crews call this the fire behavior triangle.
Dry brush burns faster than green timber. Wind doesn't just fan a fire; it throws embers ahead of it, sometimes more than a mile, starting new fires before anyone's even reached the first one. And slope changes everything. Add just 10° of upward tilt to the ground and a fire's speed can double because heat rises and rising heat means the fuel just ahead of the flames is already drying out and getting ready to ignite before the fire even arrives. Under the wrong conditions, a wildfire can move across ground at 14 mph — faster than most people can run. About one in five wildland fires starts from lightning, usually in the kind of remote, tangled backcountry where nobody sees the strike happen. The rest start from people, sometimes on purpose, mostly by accident: a spark from a chain, a campfire that wasn't quite out, a powerline swinging in the wind.
All of it gets coordinated from the top down through something called the incident command system, or ICS, a standardized management framework used across every major wildfire response in the country. Behind all of that coordination, tracking resources, issuing certifications, and managing the national response picture, sits the National Interagency Fire Center, NIFC, based in Boise, Idaho. A hotshot crew is typically 20 to 30 firefighters led by a superintendent, a couple of assistant superintendents, and a handful of squad leaders. At least 80 percent of the crew has to have a full season or more of prior experience. Smokejumpers deploy from aircraft in loads of eight to 20 jumpers depending on the airframe. Helitack crews range from about seven to 24 people. Single-engine air tankers, often converted agricultural planes, carry around 800 gallons and work smaller, more precise jobs. Type 1 and Type 2 air tankers carry anywhere from 1,800 to 5,000 gallons. At the top of the scale sit the very large air tankers (aircraft like the DC-10) capable of dropping more than 8,000 gallons of retardant in a single pass, enough to lay down a firebreak hundreds of feet wide in seconds. When wildfire activity spikes and the contracted fleet can't keep up, the military steps in with modular airborne firefighting systems, turning C-130 cargo planes into air tankers that can each carry about 3,000 gallons.
Lead planes fly low and just ahead of the tankers, showing pilots exactly where to drop. Air tactical aircraft circle higher up, coordinating the whole aerial dance so that a sky full of aircraft moving at very different speeds doesn't turn into its own disaster. Water and retardant almost never get dropped directly onto the flames. Instead, they get placed ahead of the fire or along its flanks, building a chemical firebreak that slows the fire down and buys the people on the ground enough time to actually reach it and finish the job. Retardant — the reddish-pink stuff you've probably seen falling out of the sky in wildfire footage — works because of what it does to the fuel itself, coating it so it resists ignition even after the flame front arrives. The most widely used brand is Phos-Chek, a phosphate-based compound that's become so common its name is almost synonymous with aerial retardant. It was never meant to put a fire out on its own. It's meant to hold the door open long enough for the ground crews to walk through it. Their main weapon isn't water. It's a fire line, a stripped-bare corridor of dirt cut by hand tools and chainsaws, wide enough that fire runs out of fuel when it reaches it.
A wildfire that grows large enough to need all of them at once is being fought as a system, managed through the incident command system from the ground up. Aircraft slow it down and buy time. Hand crews and hotshots use that time to cut fire line and remove fuel. Helitack and smokejumpers reach the places nothing else can get to fast enough. And overhead incident commanders are reading fuel conditions, weather forecasts, and slope maps, trying to predict where that fire behavior triangle is about to swing hardest, so they can put people in front of it instead of behind it. Communities pushing further into the wildland urban interface, the WUI (the exact zone where developed neighborhoods meet fire-prone wildland), mean the stakes of every ignition go up exponentially. In 2025, the United States recorded 77,850 wildfires, a number well above the 10-year average, even though the total acreage burned actually came in lower than normal at a little over 5 million acres. The largest single fire of that year, the Dragon Bravo fire in Arizona, burned through 145,504 acres on its own. Wildfires have more than doubled in frequency and intensity in the last two decades. Eight out of the 10 most destructive California wildfires have occurred in the last decade.
Rain's wildfire mission autonomy system perceives the fire, understands its behavior, size, direction of spread, and uses that information to design a suppression strategy. Rain's wildfire intelligence system builds a strategy that considers subsequent responding aircraft, incorporating their resources and arrival times into an optimal suppression strategy. Ground crews ensure complete fire suppression. The technology equips fire agencies with a new layer of safety for human-piloted missions, and enables efficient command of a network of uncrewed aircraft prepositioned in remote areas to reduce response time. Independent research shows that cutting wildfire response times by just 15 minutes could reduce the frequency of large, uncontained fires by 3 to 7 percent — yielding up to $8.2 billion in annual benefits for California alone. With over 1,100 early fire watch cameras in California and more across the American West, many regions recognize the growing threat of wildfire and have already invested in early detection. Rain's autonomy expands response options, enhances safety with pilot workload reduction, and allows aircraft to continue working in spite of dangerous conditions, including at night and in other degraded visual environments. A network of pre-positioned autonomous aircraft can increase the number of firefighting resources available in the earliest, most critical minutes, speed response and give firefighters additional layers of safety, and automate essential tasks like hotspot detection and perimeter control.
For applicants, this means domain knowledge isn't optional context — it's a design constraint. The autonomy stack has to reason about slope-driven acceleration, ember transport, fuel moisture gradients, and the doctrinal logic of where retardant gets placed versus where water gets dropped. It has to speak the language of ICS: division supervisors, air tactical group supervisors, helibase managers. It has to model the same fire behavior triangle that a Fire Behavior Analyst (FBAN) calculates by hand using NWCG courses S-490, S-491, and S-590, with the added requirement that the output feeds a suppression strategy a human incident commander can trust. Rain and Sikorsky demonstrated this over live fire in California, showing communication interoperability of an autonomous aircraft with a human-piloted helicopter in the same Fire Traffic Area, supervised by an Orange County Fire Authority air tactical group supervisor aircraft. Rain and Brothers Air Support are integrating Rain's wildfire perception system onto private firefighting aircraft — the first time Rain's system has been integrated with a private operator. Rain and Sikorsky also demonstrated how an autonomous Black Hawk helicopter can be commanded to take off, identify the location and size of a small fire, and then accurately drop water to suppress the flames. Candidates who cannot translate fire behavior physics into software requirements, or who don't understand why a 15-minute response-time delta changes the strategic picture, will not pass the screen. The mission demands fluency in both the physics and the doctrine.
Culture Fit: "Find A Way" Is a Filter, Not a Slogan
Rain Aero's careers page states it plainly: "We are guided by the phrase, 'Find A Way.' We expect to frequently encounter enormous challenges and choose optimism." That sentence functions as a filter. Candidates who read it and feel friction self-select out before a recruiter spends a minute on their resume.
The mission itself is the first screen. Every public job posting leads with: "You're excited about Rain's mission to stop wildfires before they grow out of control." The research backs the urgency: that trend over two decades; eight of the ten most destructive California fires burned in the last decade; smoke-related premature deaths could reach nearly 2 million cumulatively in the U.S. over 30 years. Rain's leadership frames the work as "creating essential infrastructure for billions of people to coexist with climate change."
Fire-service credibility runs through the culture. The company notes: "We have personal experience with catastrophic wildfire. We're solving our own problem. Our team has worked alongside fire professionals since day one." That isn't rhetoric — it's a hiring signal. The same job postings list "You've served as a firefighter" as a standout qualification. Former CAL FIRE Chief Deputy Director Christopher Anthony, Orange County Fire Authority Chief Brian Fennessy, and former State Fire Marshal Kate Dargan Marquis have all gone on record validating Rain's approach.
The "Find A Way" values translate into concrete working conditions that act as cultural filters. The Alameda office is on-site, five days a week, accessible by ferry, bike, and ample parking, a deliberate choice for a team that "appreciates in-office time, strives to make the most out of very few meetings and enjoys constantly learning and sharing what we know." Travel of at least 15 percent per year for validation testing is non-negotiable. That requirement appears in every engineering posting.
Small-team ownership is explicit: "You thrive in small teams, where you can see the immediate impact of your knowledge and expertise." At roughly 50 people, every hire changes the culture's center of gravity. The company says it values "the depth of our relationships forged through collectively overcoming these challenges" and "we take turns taking out the garbage."
Mission-driven resilience shows up in the technical standards Rain adopts voluntarily. Familiarity with STANAG/DoD autonomy standards and DO-178C appears as a preferred qualification across roles. Those are defense-grade safety frameworks, not typical startup fare. Choosing them before regulators require them signals a culture that treats "mission-critical" as a design principle, not a compliance milestone.
The Sikorsky and Brothers Air Support partnerships reinforce the cultural narrative. Demonstrating autonomous wildfire suppression from a Black Hawk with that same supervisor in the loop is not a demo day stunt. It's the operational reality Rain's engineers build toward.
Application Process: Getting Past the Screen and the Interview
Rain Aero's hiring volume means your resume hits an ATS before a human sees it. Most aerospace employers use Workday or Taleo, and parser-safe files are non-negotiable. Multi-column Canva exports scramble job titles and dates in Workday imports. Taleo surfaces keyword matches to hiring managers fast but still needs clean section headers. Submit a single-column PDF with selectable text, 10–12 pt readable fonts, and month-year dates inline with role titles. DOCX is safer for some Workday portals. Run a text-select check and a plain-editor paste test before you apply.
Semantic matching weighs context, not keyword counts. Pull 8–12 terms from the specific Rain Aero posting (ROS 2, C++, Python, DO-178C, simulation frameworks, UAV autonomy, fire behavior modeling) and weave them into your summary, skills block, and at least two experience bullets. Repeating the same skill ten times does not beat 2026 ATS ranking. Write for humans; let keywords appear where they are true. If the role emphasizes perception stack integration, reflect that language without overstating authority you do not hold.
Every metric on the page should be expandable into a 60–90 second story with context, constraints, and tradeoffs. If you cannot explain the number in an interview, soften or replace it.
Quantify bullets with scope: team size, budget, volume, error rates, cycle time. "Reduced perception latency 18% on a 12-node ROS 2 stack processing 4K sensor data at 30 Hz" beats "improved perception performance." Modern aircraft are flying data centers; even mechanical engineers need coding skills now. List Python, C++, MATLAB, and simulation tools (Gazebo, AirSim, custom frameworks) with hands-on depth. If you have an active Secret or Top Secret clearance, put it at the very top; it is a massive hiring advantage in aerospace.
Portfolio evidence matters when NDAs allow. Bring anonymized dashboards, redacted reports, or process maps. For regulated aerospace work, describe outcomes in aggregate without confidential identifiers. A GitHub link showing a ROS 2 autonomy demo or a simulation environment you built carries more weight than a skills bar chart. Self-rated skill bars rarely help aerospace hiring teams and often break parsing.
Interview alignment starts with the resume. Interviewers in aerospace often probe the strongest bullet first, so make sure it is your best true story. Prepare one-minute STAR stories for your top three metric bullets. Common themes will include perception/autonomy integration, safety-critical software lifecycle (DO-178C or ISO 26262), simulation-to-reality gap closure, and wildfire operational constraints. Expect a walkthrough of your most relevant project. Bring a one-page metric cheat sheet to stay consistent with the resume.
Red flags kill offers: numbers that shift between resume, LinkedIn, and conversation; titles inflated beyond what HR can verify; tools listed without hands-on depth. Small inconsistencies trigger recruiter doubt in roles where credential checks are standard. Track which resume version went to each employer. If you apply internally at Rain Aero, still tailor to the new family, because internal ATS searches use the same keyword logic as external applicants.
Ask questions that signal you understand how the function operates. How is success measured in the first 90 days? Which simulation and CI/CD systems does the team use daily? How does the Workday workflow handle referrals versus cold applications? Strong questions separate candidates who want the mission from candidates who want a job.
The bar is high. Your resume is the script recruiters use to open interviews. Make every line earn its keep.
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