New opportunity

Custom Software Engineer

Accenture · Bengaluru, India

About this role

Accenture's Next Gen Robotics Team is seeking a Senior lead to drive next-generation robotics innovation at the intersection of technology, industry, and society. The role focuses on developing and delivering scalable robotics solutions, including AMRs, autonomous drones, quadrupedal robots, and AI-powered robotic systems, for global industrial clients. The candidate will provide strong technical leadership and lead interdisciplinary teams of 3–10 professionals across PoC, pilot, and rollout phases to deliver real-world robotics applications that improve efficiency, safety, and intelligence.

Responsibilities

Provide technical leadership for robotics innovation projects, including architecture, implementation, integration, and deployment for global industrial clients.
Design and develop scalable robotics architectures focused on autonomy, Physical AI, AI integration, real-time systems, and simulation.
Lead interdisciplinary delivery teams of 3–10 people across PoC, pilot, and production rollout phases.
Drive technology evaluations, benchmarking, venture screening, and the development of robust robotics demonstration and test environments.
Collaborate closely with clients, technology partners, and Accenture industry teams to define roadmaps and transition robotics solutions into productive implementations.
Contribute to the Next-Gen Robotics strategy, including technology roadmaps, partner ecosystem development, innovation initiatives, and internal technical enablement.
Provide technical guidance and mentorship to robotics engineers and contribute to the development of robotics capabilities within the Centre of Excellence (CoE).

Required qualifications

Minimum 5 years of relevant experience in robotics, consulting, software engineering, or technically focused engineering projects.
Strong academic background in Robotics, Computer Science, Engineering, or a related discipline.
Hands-on expertise with modern robotics technology stacks, including ROS2, motion planning, sensor fusion, and robotics simulation using NVIDIA Isaac Sim, MuJoCo, or Gazebo.
Strong software development expertise in Python and C++.
Experience with clean-code practices, Git, CI/CD, software architecture, and engineering best practices.
Strong understanding of AI/ML, Computer Vision, robotics design, autonomous systems, and simulation.
Demonstrated experience working as a Robotics Architect, Lead Engineer, Technical Lead, or Integrative Technology Specialist in interdisciplinary environments.
Strong technical communication skills and English proficiency at C1 level or above.
Minimum 15 years of full-time education.

Preferred qualifications

Master's or PhD degree.
Experience with Physical AI platforms and integration of humanoid or quadrupedal robots.
Experience with autonomous systems such as AMRs, autonomous drones, or AI-powered service robots.
Exposure to venture screening, technology scouting, technology benchmarking, or emerging robotics ecosystem evaluation.
Consulting or client-facing experience within industrial automation, manufacturing, automotive, life sciences, or other industrial domains.
Experience in developing robotics PoCs and transitioning them into pilot and production environments.
Experience with robotics technology strategy, partner ecosystem development, or Centre of Excellence (CoE) initiatives.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

RoboticsROS2Motion PlanningSensor FusionNVIDIA Isaac SimMuJoCoGazeboPythonC++AI/MLComputer VisionAutonomous SystemsIndustry X Security

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Technical Leadership of Robotics Delivery
The role requires leading interdisciplinary teams of 3-10 professionals through the full lifecycle of robotics projects, from Proof of Concept (PoC) to production rollout. You must demonstrate the ability to guide architecture, implementation, and integration while ensuring the final solution meets industrial-grade standards for efficiency and safety.
Scalable Robotics Architecture Design
You are expected to design and develop robust architectures for autonomous systems, including AMRs, drones, and quadrupedal robots. This requires deep expertise in ROS2, motion planning, sensor fusion, and simulation environments like NVIDIA Isaac Sim or Gazebo, ensuring that prototypes can be successfully transitioned into scalable, real-world industrial applications.
Strategic Innovation and Ecosystem Development
Beyond project delivery, you must contribute to the Next-Gen Robotics strategy by performing technology benchmarking, venture screening, and partner ecosystem development. This involves collaborating with global clients and internal teams to define roadmaps and build capabilities within the Centre of Excellence (CoE).

Likely challenges to think through

Bridging the Gap Between PoC and Production
A common difficulty in industrial robotics is the 'pilot purgatory' where prototypes fail to scale due to environmental variability or lack of robustness. Prepare by discussing specific strategies for hardening code, managing edge cases in real-world deployments, and ensuring your simulation-to-reality (Sim2Real) pipelines are reliable.
Managing Interdisciplinary Stakeholder Expectations
As a lead, you will interface between technical engineering teams and non-technical industrial clients. The challenge lies in translating complex robotics constraints into clear business value. Prepare by practicing how to communicate technical risks, such as sensor limitations or latency issues, in a way that aligns with client project timelines and safety requirements.

Practice your answers

Technical practice

Designing Scalable Robotics Architectures

What to coverExplain your approach to designing a robotics architecture that balances autonomy, real-time performance, and AI integration. Discuss how you ensure modularity and scalability when transitioning from a Proof of Concept (PoC) to a full-scale industrial production environment.

ROS2 and Middleware Implementation

What to coverDescribe your experience with ROS2 in complex, multi-robot or high-stakes industrial settings. Focus on how you manage node communication, lifecycle management, and security considerations within a distributed robotics system.

Simulation-to-Reality (Sim-to-Real) Pipelines

What to coverHow do you leverage tools like NVIDIA Isaac Sim, MuJoCo, or Gazebo to validate robotics systems before physical deployment? Discuss the challenges of bridging the gap between simulation results and real-world performance, particularly regarding sensor noise and environmental variability.

Motion Planning and Control Strategies

What to coverDiscuss your experience implementing motion planning algorithms for autonomous systems such as AMRs or quadrupedal robots. Explain how you handle dynamic obstacle avoidance and path planning in unstructured or changing industrial environments.

Sensor Fusion for Autonomous Systems

What to coverDetail your methodology for integrating data from disparate sensors (e.g., LiDAR, cameras, IMUs) to achieve robust localization and perception. Explain how you handle sensor calibration and data synchronization in real-time robotics applications.

AI and Computer Vision Integration

What to coverHow do you integrate AI/ML models into a robotics stack to enhance system intelligence? Address the trade-offs between edge-based processing and cloud-based inference in terms of latency, bandwidth, and reliability.

CI/CD for Robotics

What to coverDescribe how you implement CI/CD pipelines for robotics software to ensure code quality and reliable deployments. Explain how you incorporate automated testing, including unit tests and simulation-based regression testing, into your development workflow.

Physical AI and Embodied Intelligence

What to coverWhat is your perspective on the current state of Physical AI in industrial robotics? Discuss how you approach the integration of AI models that directly control physical hardware, focusing on safety, predictability, and system stability.

Behavioural practice

Leading Interdisciplinary Teams

What to coverDescribe a situation where you led a team of 3–10 professionals with diverse technical backgrounds to deliver a robotics project. How did you manage communication, align technical goals, and ensure the team met project milestones during the PoC or rollout phase?

Managing Client Expectations and Roadmaps

What to coverProvide an example of how you collaborated with a client to define a robotics roadmap. How did you handle conflicting requirements or technical limitations while ensuring the final solution met the client's business objectives?

Mentorship and Capability Building

What to coverShare an experience where you provided technical guidance or mentorship to junior robotics engineers. How did you contribute to the development of a Centre of Excellence (CoE) or internal technical enablement within your organization?

Technology Benchmarking and Decision Making

What to coverDescribe a time you had to evaluate emerging robotics technologies or vendors for a specific industrial application. How did you conduct the benchmarking process, and what criteria did you use to justify your final recommendation to stakeholders?

Sharpen your knowledge

Topics to prepare

Scalable Robotics Architecture
Focus on designing systems that transition from Proof of Concept (PoC) to full-scale industrial production. Review architectural patterns for real-time autonomous systems, ensuring modularity, reliability, and integration with existing industrial infrastructure.
Physical AI and Simulation Strategy
Understand the integration of AI models into physical robotic hardware. Study how to leverage simulation environments like NVIDIA Isaac Sim or Gazebo to validate autonomous behaviors before physical deployment, which is critical for the role's focus on innovation and risk mitigation.
Technical Leadership in Interdisciplinary Teams
Prepare to discuss your experience leading teams of 3-10 professionals. Focus on methodologies for mentoring engineers, managing technical roadmaps, and facilitating communication between technical teams and non-technical industrial clients.

Skills to revise

ROS2 and Motion Planning
Practice implementing complex motion planning algorithms within the ROS2 framework. Ensure you can articulate how to optimize path planning for specific robotic platforms like AMRs or quadrupedal robots in dynamic industrial environments.
Sensor Fusion and Computer Vision
Review techniques for integrating data from multiple sensors (LiDAR, cameras, IMUs) to achieve robust localization and perception. Be prepared to explain how these inputs inform autonomous decision-making in real-world industrial settings.
C++ and Python for Robotics
Demonstrate proficiency in writing clean, maintainable code for robotics applications. Focus on C++ for performance-critical real-time control loops and Python for rapid prototyping, AI integration, and scripting within the robotics stack.

Your preparation checklist

Prepare a robotics project portfolio walkthrough
Select a past project where you led a team through the full lifecycle from PoC to production. Prepare to discuss your specific role in system architecture, your choice of simulation tools like NVIDIA Isaac Sim or Gazebo, and how you managed technical trade-offs in ROS2-based environments.
Demonstrate technical leadership in interdisciplinary teams
Prepare concrete examples of how you mentored junior engineers and managed teams of 3-10 professionals. Focus on your methodology for technical decision-making, resolving integration conflicts, and ensuring code quality through CI/CD and clean-code practices.
Develop a strategy for industrial robotics deployment
Be ready to explain your approach to benchmarking emerging robotics technologies and venture screening. Prepare a brief framework for how you would evaluate a new autonomous system (e.g., AMRs or drones) for a global industrial client, considering scalability, safety, and AI integration.
Formulate questions regarding the Centre of Excellence (CoE)
Prepare thoughtful questions about Accenture's current robotics CoE initiatives. Ask about how the team balances internal technical enablement with client-facing delivery, or how the firm approaches partner ecosystem development for next-generation robotics.

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