Roles & Responsibilities :Working closely with the CTO and members of technical staff to meet deadlines.Working with an agile team to setup and configure GitOps (CI/CD) based pipelines on GitLabCreate and deploy Edge AIoT pipelines using AWS Greengrass or Azure IoTDesign and develop secure cloud system architectures in accordance with enterprise standardsPackage and automate deployment of releases using Helm chartsAnalyze and optimize resource consumption of deploymentsIntegrate with Prometheus, Grafana, Kibana etc. for application monitoringAdhering to best practices to deliver secure and robust solutionsRequirements :Experience with Kubernetes and AWSKnowledge of cloud architecture concepts (IaaS, PaaS, SaaS)Knowledge of Docker and Linux bash scriptingStrong desire to expand knowledge in modern cloud architecturesKnowledge of System Security Concepts (SAST, DAST, Penetration Testing, Vulnerability analysis)Familiarity with version control concepts (Git)

Role: Senior Solution Architect Computer Vision Experience: 6+ years Role Overview: TheSenior Solution Architect will be responsible for designing, developing, and deploying large-scale, real-time vision solutions for object detection, pattern recognition, behavior analysis, and intelligence augmentation. This role demands a deep technical understanding of computer vision, machine learning, and AI infrastructure, combined with strong leadership capabilities. The architect will collaborate with cross-functional teams to translate business needs into robust technical solutions while ensuring efficiency, scalability, and innovation. Key Responsibilities: 1. Solution Architecture & Technical Leadership: Design and implementscalable, high-performancecomputer vision solutions for complex business challenges. Architect real-timeimage and video processing pipelines, integrating technologies for object detection, tracking, and behavior analysis. Developfault-tolerant, distributed systemsusing state-of-the-art deep learning and image processing techniques. Driveend-to-end system optimization, includingdata pipelines, model inference efficiency, and GPU utilization. Evaluate and integrate cutting-edge AI frameworks, edge computing strategies, and cloud-based vision services. 2. Project Leadership & Execution: Definetechnical strategy and roadmapfor delivering vision-based AI solutions. Ownend-to-end project execution, from requirement gathering to deployment. Develop comprehensivesolution blueprints, architecture documentation, and execution plans. Ensurealignment with business goals, cost-effectiveness, and system reliability. Set and managestakeholder expectations, ensuring timely and successful project delivery. 3. Collaboration & Cross-Functional Engagement: Work closely withAI research teams, data engineers, software engineers, and product managersto align technical designs with business objectives. Collaborate withcloud infrastructure, DevOps, and MLOps teamsto ensure smooth deployment and monitoring of vision pipelines. Partner withhardware teamsfor optimizing computer vision models for edge devices and embedded systems. 4. Mentorship & Team Development: Mentor and trainjunior and mid-levelcomputer vision engineers to build strong technical capabilities. Establish and enforcebest practices for AI model development, deployment, and monitoring. Foster a culture ofinnovation, knowledge sharing, and technical excellencewithin the team. Skills & Qualifications: Technical Expertise: Strong proficiency in Python and Linux, with expertise in writingoptimized, fault-tolerant code. Deep understanding ofimage processing and computer visiontechniques. Experience with libraries such asOpenCV, NVIDIA CUDA, Intel OpenVINO, TensorFlow, PyTorch, and NumPy. Expertise inmachine learning, deep learning, and AI model optimizationfor real-time inference. Strong knowledge ofMLOps, model monitoring, and lifecycle management. Experience withedge AI deployment and optimizations for embedded systems (Jetson, TPU, FPGA, etc.). Soft Skills: Ability totranslate complex business challenges into scalable AI solutions. Strongcommunication and collaborationskills across technical and non-technical teams. Provenleadership skills, including mentoring, team management, and decision-making. Innovative mindset, with a passion for staying ahead of the curve in AI and vision technologies. Preferred Experience: Prior experience inlarge-scale vision automation solutions, ideally infast-paced startup environments. Track record of successfully architecting anddeploying computer vision solutions from concept to production. Experience withedge computing, federated learning, and privacy-preserving AI techniques. Contributions toopen-source AI/computer vision projectsor relevant publications in the field.