By Jakub Tomaszewski, senior robotics engineer at SoftServe
My path as a robotics engineer began in 2020, and whereas my introduction to the world of robotics wasn’t that way back, the work I’ve executed and the business itself has permuted and developed a lot in simply six years.
Again then we wrote each line of code by hand, teammates reviewed it intimately, and points took longer to repair. Stack Overflow was usually the primary place to search for an answer, and avenues for studying spanned throughout books, analysis papers, Google, and YouTube.
At this time, AI can speed up a lot of that work. Writing code, diagnosing issues, and studying extra about an unfamiliar idea can all occur quicker. However that doesn’t essentially make the senior engineer’s position less complicated.
As implementation turns into simpler to speed up, extra weight shifts towards understanding the entire system: deciding the way it ought to be designed, integrating its components, validating whether or not it really works, and understanding when an apparently appropriate answer is definitely incorrect.
That’s the reason I believe the definition of a robotics engineer is altering. On this article, I’ll clarify what abilities and foundations matter most to senior robotics engineers in 2026.
What abilities matter for senior robotics engineer in 2026
Robotics has all the time mixed completely different disciplines, however the stage of their integration is far greater now. Higher {hardware} acceleration, extra succesful simulation environments, and AI are altering each what we construct and the way we construct it. I see 4 areas which have both expanded considerably or turn out to be way more necessary.
1. Interdisciplinary information and system integration
These abilities have expanded quite a bit as a result of robotics more and more connects mechanics, electronics, management, notion, software program structure, and validation.
On the similar time, AI and {hardware} acceleration are shifting senior, lead, and architect roles towards structure, integration, and validation somewhat than remoted implementation duties.
This issues when constructing full programs. For instance, a digital twin requires a 3D mannequin of the robotic, a physics description, sensor configuration, and a telemetry path from the true machine.
2. Simulation
Simulation has moved from a supporting exercise to a core engineering technique. We use it to design, check and decrease dangers earlier than we even contact machines.
This grew to become extra necessary as a result of bodily testing is slower, expensive, and generally a lot much less protected, whereas computing energy and simulation instruments have improved considerably.
Excessive-fidelity simulation can be utilized to review advanced robotic programs earlier than committing to {hardware}, whereas co-simulation permits us to attach a high-fidelity mannequin of a nonlinear system with a robotics simulator equivalent to Nvidia Isaac Sim.
3. Bodily AI and reinforcement studying
Bodily AI and reinforcement studying have moved from analysis nearer to every day engineering apply as robots are anticipated to function in altering environments.
Reinforcement studying could make a controller extra strong in altering and stochastic situations, whereas Bodily AI expands the position of AI from software-only duties to programs that understand, act, and work together with the bodily world.
For a senior engineer, this implies understanding the way to combine learning-based approaches with classical robotics strategies as a substitute of retaining them separate.
4. Artificial information and digital twins
These competence areas have turn out to be extra related as a result of gathering real-world information and testing on bodily programs might be costly and time-consuming.
Artificial information can speed up laptop imaginative and prescient and imitation studying when labeled actual information is scarce, whereas digital twins make it attainable to mannequin and examine a robotic system earlier than or alongside work with the true machine. Each depend upon sturdy integration between simulation, fashions, sensors, and the bodily system.
Begin with an issue
For an skilled engineer, the best strategy is to begin with a concrete technical downside somewhat than attempting to be taught a brand new area in isolation.
Set a transparent objective, determine the information gaps, and use probably the most related assets, equivalent to analysis papers, technical documentation, discussions with colleagues, and AI to navigate the huge quantity of accessible info and speed up the training course of.
The necessary half is to use the brand new information instantly in engineering work or laboratory experiments. This makes it attainable to check whether or not you truly perceive the idea and the place the remaining gaps are.
What foundations stay important for a senior robotics engineer?
Arithmetic and robotics idea stay important. I discover it tough to think about a robust robotics engineer who has not spent hundreds of hours on the fundamentals.
If somebody claims that AI can substitute that basis, I’d reply that it could actually, till it can’t. Every day I appropriate AI when it writes arithmetic or implements a robotics idea within the incorrect approach.
These fundamentals are additionally the constructing blocks of structure. A robotic system is an meeting of kinematics, dynamics, estimation, management, notion, and software program interfaces.
If an engineer can’t choose whether or not a mannequin is properly posed, whether or not a controller is steady, or whether or not a sim-to-real hole is suitable, structure turns into a drawing with out physics. Instruments change; the necessity to motive concerning the plant doesn’t.
For me, that basis got here by specialised college training after which continued by apply and self-study. For my engineering thesis, I designed and constructed a manipulator from scratch.
Later, throughout my grasp’s research in Embedded Robotics, I continued working with extra superior robotics issues. I nonetheless return to mathematical fashions, derivations, and analysis papers when a undertaking calls for it.
I additionally began a PhD targeted on fusing classical management idea with AI. It forces me to maintain the speculation sharp whereas exploring how classical management and newer AI strategies can work collectively in apply.
How has seniority in robotics developed lately?
Seniority was once described primarily by onerous abilities like programming languages, frameworks, and years of supply.
These nonetheless matter, and at SoftServe, robotics roles proceed to ask for sturdy arithmetic, C++ or Python, ROS2, simulation instruments equivalent to Isaac Sim or Gazebo, and the flexibility to check each in simulation and on {hardware}. However at the moment I’d not outline a senior robotics engineer by a know-how guidelines.
For me, seniority is outlined as a lot by skilled habits as by technical experience. Lately, the senior bar has moved from implementing a part properly towards proudly owning a system, integrating it, validating it, and speaking the end result. Traits and capabilities a senior robotics engineer ought to embody embrace:
- Communication and decision-making. It’s good to clarify structure to a undertaking supervisor, a consumer, and management, usually with completely different ranges of technical background. You need to be capable of suggest a choice, defend it with proof, and nonetheless pay attention when someone challenges it.
- Self-discipline and steady studying. The area doesn’t pause. Specialists should adapt to new frameworks, simulators, and AI strategies whereas supply dates turn out to be shorter and expectations round AI acceleration develop.
- Possession and engineering judgment. Robotics combines uncertainty in {hardware} with strain on time. A senior engineer ought to be capable of end a process or a undertaking with out shut steerage, make trade-offs, and maintain the standard of the work.
- Interdisciplinary expertise. The senior position is constructed by working throughout blended areas of experience, equivalent to digital twins, multi-robot co-simulation, underwater automobiles, industrial manipulators, drones, and laboratory {hardware}. That selection teaches the place a way is relevant and the place it’s not, in addition to the way to collaborate with specialists from neighboring fields.
- System-level accountability. AI has accelerated the implementation a part of engineering. It has not eliminated the necessity to personal the system, combine it, validate it, and talk the end result.
Why working with {hardware} issues for a senior robotics engineer
For all of the modifications in how robotics engineers work at the moment, {hardware} stays the place engineering judgment is examined. {Hardware} teaches you what simulation can’t: which assumptions survive contact with the true world.
Sensors have noise, cameras have imperfect calibration, actuators have limits and delays, and each robotic has mass, inertia, friction, and suppleness {that a} simulator might simplify.
Simulation continues to be invaluable for designing architectures and trajectories, working exploratory research, and testing situations which might be unsafe or tough to breed within the lab.
In our workforce, we mix this simulation-first strategy with hands-on work in our Robotics Labs in Lviv and Wrocław. Engineers can transfer from prototypes to built-in programs and validate them on actual {hardware}, together with humanoids, robodogs, industrial robotic arms, and different autonomous programs.
This bodily entry issues as a result of earlier than going from sim to actual, we want mannequin identification and validation on {hardware}, the place the remaining gaps turn out to be seen.
That, for me, comes again to what it means to turn out to be a senior robotics engineer at the moment. AI can speed up coding, simulation can speed up testing, and new instruments can shorten growth cycles, however somebody nonetheless has to grasp the system properly sufficient to know whether or not the end result will work outdoors the digital surroundings.
Concerning the writer: Jakub Tomaszewski is a senior robotics engineer at SoftServe. He focuses on simulation, digital twins, co-simulation, superior management, and Bodily AI. He’s additionally a PhD scholar at Wrocław College of Science and Know-how, the place he research the fusion of classical management and AI for wheeled bipedal robots.
Principal picture by way of Straightforward-Peasy.ai
