Job Summary:

• The Data Architect / Solution Architect (Data Platform) will be the mastermind behind the technical architecture of our next-generation Data Management and Processing Platform. This role is responsible for designing scalable, highly secure, and cost-effective cloud/hybrid storage systems alongside automated data pipelines capable of handling petabytes ($PB$) of unstructured multimedia data (e.g., massive egocentric video streams, audio, and sensor logs for humanoid robot training). 

• The ideal candidate will bridge the gap between traditional enterprise big data infrastructure and advanced AI engineering. You will architect high-throughput pipelines that leverage Computer Vision, Vision-Language Models (VLMs), and Vision-Language-Action (VLAs) models for automated data pre-processing, semantic scene cutting, and pre-labeling. Concurrently, you will ensure that the underlying data management infrastructure and data governance layers scale in perfect parallel to support this heavy computing throughput, while maintaining rigorous anti-copying security controls. 

KEY RESPONSIBILITIES:

• End-to-End Architecture Design: Design and implement the core data platform architecture, including data ingestion, stream/batch processing, petabyte-scale storage, and seamless data delivery layers. 

• AI-Driven Pipeline Integration (Vision/VLM/VLA): Architect and build high-throughput ETL/ELT pipelines that integrate state-of-the-art AI models (Computer Vision, VLMs, VLAs) to automate data pre-processing. This includes automated video curation, filtering out low-quality/redundant frames, semantic scene indexing, and automated pre-labeling of "Action Atoms" before human QA/QC verification. 

• Parallel Infrastructure Scaling: Design a framework where data processing compute power (GPU/CPU clusters for AI model inference) and data management storage/cataloging infrastructure scale seamlessly in parallel. Ensure zero bottlenecks as data volume expands towards the petabyte scale. 

• Storage Optimization & Cost Management: Optimize cloud storage topologies (primarily AWS S3 and hybrid cloud solutions) to achieve ultra-low storage costs for 2000TB+ environments, utilizing smart lifecycle policies, tiering (Glacier), and efficient indexing. 

• Secure Data Governance & Anti-Copying Solutions: Implement robust Data Governance, Identity and Access Management (IAM), and Confidential Computing frameworks. Design mechanisms (e.g., secure streaming, DRM, or sandboxed environments) that allow cross-functional teams (PO, BA, QA/QC, AI Engineers) to process and validate data without being able to download or make unauthorized local copies. 

• Cross-functional Alignment: Collaborate closely with the Head of Data Acquisition, POs, BAs, and AI Research teams to translate data collection business requirements and client specs into solid, future-proof technical blueprints. 

JOB REQUIREMENTS:

Relevant education and experience:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related technical field. Professional certifications (e.g., AWS Certified Data Engineer, AWS Solutions Architect Professional, or Google Cloud Professional Data Architect) are highly preferred. 

• Core Technical Experience: 

  • Minimum of 5+ years of experience in Data Architecture, System Architecture, or Senior Data Engineering, with a proven track record of building large-scale data platforms. 

  • Strong experience with Big Data processing frameworks and ecosystems (such as PySpark, Apache Spark, Hadoop) and Python programming. 

  • Hands-on mastery of Cloud Infrastructures (AWS preferred: S3, EC2, IAM, Lambda, Athena, EMR). 

• AI & Multimedia Pipeline Orchestration: Proven experience orchestrating AI inference within distributed data pipelines (deploying Vision models, VLMs, or LLMs at scale using frameworks like Ray, Triton Inference Server, or Kubernetes) to process high-volume unstructured video/audio data.

• Enterprise Security Background: Direct experience in setting up enterprise-grade data security, access control, and data loss prevention (DLP) frameworks. 

Preferred Qualifications:

• Preferred Qualifications: Experience in building data platforms specifically for Autonomous Vehicles, Robotics, Computer Vision AI, or Large Multi-Modal Model (LMM) R&D startups is a massive advantage. 

• Composed & Analytical Mindset: Exceptionally composed and methodical under pressure. Able to systematically diagnose distributed computing bottlenecks, model inference latency, system failures, or security vulnerabilities and deliver structural architectural fixes. 

• Forward-Thinking & Scalability-Obsessed: Always designs systems with tomorrow's scale in mind, focusing on automation, infrastructure-as-code, and eliminating single points of failure through parallel scaling. 

• Collaborative Communicator: Capable of breaking down highly complex architectural and AI concepts into clear, understandable business terms for non-technical stakeholders (Ops, Clients, Managers). 

Personality/ Attitude:

• Exceptionally Composed under Complexity & Pressure: Maintains absolute calm, mental clarity, and a methodical approach when dealing with system failures, high-stakes security threats, model inference latencies, or tight deployment deadlines. 

• Parallel & Scalability-Obsessed Mindset: A forward-thinking engineer who naturally rejects short-term, manual patches. Driven by a passion for automation, infrastructure-as-code, and designing parallel systems that eliminate single points of failure. 

• Analytical & Deeply Structural Troubleshooter: Possesses an uncompromising, root-cause-analysis approach to problem-solving. Able to isolate bottlenecks systematically across distributed computing clusters, cloud storage layers, or complex AI models. 

• Collaborative & Articulate Communicator: Exceptional ability to translate highly dense architectural blueprints, data governance risks, and VLM/VLA capabilities into clear, actionable business insights for non-technical stakeholders (Ops teams, Product Owners, and clients). 

• Security-First Integrity: Demonstrates an unyielding commitment to data privacy, intellectual property protection, and secure infrastructure design, ensuring anti-copying frameworks are never compromised for convenience. 

BENEFITS:

• Highly competitive executive salary package tailored for Senior/Lead Architectural roles. 

• Deep technical ownership over a cutting-edge, petabyte-scale AI & Robotics data infrastructure from the ground up. 

• Premium private health insurance, top-tier hardware provisions (including access to high-performance compute resources), and flexible work opportunities. 

• Direct exposure to the most advanced AI and Humanoid Robotics training data paradigms in the region.