Solutions Architect

Key Responsibilities: As an Edge & IoT Solutions Architect, you will work: -

• Collaborate with clients to gather requirements, understand business objectives, and translate them into technical specifications for the engineering team.
• Design innovative Edge & IoT solutions, incorporating AI/ML components and leveraging cloud platforms such as Azure, AWS, and GCP.
• Contribute and lead the development of Edge & IoT accelerators and PoVs.
• Design, select, and deploy various IoT hardware components such as sensors, cameras, embedded devices, gateways, and servers, considering factors like power consumption, connectivity, interoperability, and environment constraints.
• Develop and present solution architecture and design documents, including diagrams, data flowcharts, and system requirements.
• Collaborate with engineering teams to ensure proper implementation of the designed solutions and provide technical guidance throughout the project lifecycle.
• Act as a mentor for team members, providing guidance, sharing knowledge, and fostering a collaborative and supportive learning environment within the Edge & IoT team.
• Act as a subject matter expert in Edge & IoT technologies, staying abreast of industry trends, emerging technologies, and best practices.
• Support the account team in the pre-sales process by providing technical assistance and inputs into solution proposals.
• Contribute to thought leadership initiatives and actively participate in internal trainings and knowledge-sharing sessions.

• Strong knowledge of IoT protocols such as MQTT, CoAP, and AMQP.
• Proficiency in edge computing technologies and platforms such as Azure IoT Edge, AWS Greengrass, or Google Edge IoT Core.
• Solid understanding of AI/ML algorithms and frameworks, with experience in implementing them in Edge & IoT scenarios.
• Experience working with various IoT devices, sensors, and connectivity solutions (e.g., Wi-Fi, Bluetooth, 5G, LoRaWAN, NB-IoT, etc.).
• Familiarity with cloud-based IoT platforms like Azure IoT Hub, AWS IoT Core, and Google Cloud IoT.
• Proven experience with programming languages such as Python, C#, C/C++, or JavaScript.
• Familiarity with containerization technologies (e.g., Docker) and orchestration platforms (e.g., Kubernetes, K3S).
• Strong knowledge of networking concepts, protocols, and technologies (e.g., TCP/IP, UDP, VLAN, VPN, Ethernet, and wireless communication protocols), and experience in designing and implementing secure, reliable, and scalable network architectures for IoT and edge computing solutions.
• Familiarity with different hardware platforms such as Raspberry Pi, Arduino, NVIDIA Jetson, Intel NUC, and others, and the ability to choose the appropriate platform according to the specific requirements, constraints, and performance expectations of the solution.
• Expertise with packaging and deploying AI and ML models on edge devices using common AI frameworks such as TensorFlow, PyTorch, or ONNX Runtime, and familiarity with optimizing these models for resource-constrained environments and efficient execution at the edge.
• Experience in designing IoT and edge computing solutions that consider factors such as physical security, device management and maintenance, thermal management, and enclosure design.
• Proficiency in assessing the compatibility, interoperability, and performance of various hardware components and their integration into a comprehensive, well-structured solution architecture.
• Knowledge of industry standards, regulations, and best practices related to IoT hardware selection, deployment, and security.

• Bachelor’s or master’s degree in computer science, Engineering, or related field.
• Minimum 10-12 years of experience in designing and implementing IoT and edge computing solutions, with at least 4-5 years focusing specifically on Edge AI and/or AI/ML integration.
• Strong communication and presentation skills.
• Excellent problem-solving abilities and attention to detail.
• Ability to work independently or as part of a team.