Technical Architect

Job description

Job Title: Technical Architect - Python / Data & AI Location: Chennai, India Experience Level: 12+ Years About Straive: Straive is a market-leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains. Data Analytics & AI Solutions, Data AI-Powered Operations, and Education & Learning form the core pillars of the company’s long-term vision. The company is a specialized solutions provider to business information providers. Straive continues to be the leading content services provider to research and education publishers. Data Analytics & AI Services: Our Data Solutions business has become critical to our client's success. We use technology and AI with human experts-in-loop to create data assets that our clients use to power their data products and their end customers' workflows. As our clients expect us to become their future-fit Analytics and AI partner, they look to us for help in building data analytics and AI enterprise capabilities for them. With a client-base scoping 30 countries worldwide, Straive’s multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore. Website: [https://www.straive.com/](https://www.straive.com/) **Technical Architect** A Technical Architect (TA) at Straive plays a crucial role in designing and overseeing the technical aspects of enterprise-grade Python, Data, and AI solutions. They ensure that high-performance technical solutions align with business requirements, scale effectively, and adhere to industry standards. Core Responsibilities Technical Solution Design: - Design scalable, secure, and robust Python-based architectures (microservices, distributed data processing, and enterprise APIs) that meet business requirements. - Create architectural blueprints, system diagrams, and design documentation to communicate the technical vision. Technology Evaluation and Selection: - Evaluate and select appropriate Python frameworks, data platforms, and cloud tools (e.g., FastAPI, Django, PySpark, Celery, Databricks). - Ensure chosen technologies align with organizational standards, security policies, and future scalability needs. Managing Implementation: - Collaborate with software and data engineering teams to ensure the successful execution of the architectural design. - Provide hands-on guidance and technical direction to developers throughout the implementation lifecycle. - Monitor development progress and address technical bottlenecks or deviations in a timely manner. Technical Leadership: - Provide technical guidance, code review standards, and mentorship to senior developers and engineering teams. - Lead architectural discussions, technical decisions, and complex problem-solving sessions. - Set engineering standards, design patterns, and best practices for Python development and data pipelines. - Serve as a subject matter expert on emerging Python ecosystem trends, GenAI/LLM integrations, and modern data platforms. System Integration: - Design and implement integration strategies for complex Python applications, REST/GraphQL APIs, microservices, and enterprise data lakes. - Ensure seamless data flow, low latency, and efficient communication between backend services and front-end/third-party systems. Ensuring System Reliability & Performance: - Establish testing frameworks, profiling strategies, and quality assurance processes to address code performance and security vulnerabilities. - Implement best practices for system optimization, high availability, concurrency handling, and fault tolerance. - Monitor application performance metrics (APM), database queries, and system bottlenecks to maintain optimal uptime. Continuous Improvement & Innovation: - Identify opportunities for automated data pipelines, process optimization, CI/CD improvements, and efficiency gains. - Lead Proof-of-Concept (PoC) initiatives to evaluate new Python frameworks, AI/ML operationalization tools, and data engineering technologies. Security & Compliance: - Design and implement security measures, authentication protocols (OAuth2/JWT), and data protection standards. - Ensure enterprise solutions comply with global security standards and policies. Documentation: - Maintain comprehensive technical documentation for system architecture, API specifications, and infrastructure designs. - Keep technical documentation accessible, current, and clear for developers and business stakeholders. Stakeholder Collaboration: - Work closely with product managers, business analysts, data science leads, and client stakeholders to align tech solutions with business goals. - Translate complex Python/Data architecture concepts into business value for non-technical leadership. Risk Management: - Identify technical risks early in the architecture phase and formulate effective mitigation strategies. - Proactively resolve system design flaws, scalability limits, or tech debt issues. Quality Assurance: - Ensure solutions conform to performance benchmarks, code quality standards, and security guidelines. - Actively participate in design reviews, critical code reviews, and validation workflows. Additional Responsibilities Strategic Planning: - Contribute to Straive’s internal technology roadmap, tech stack modernization, and developer skill enablement programs. - Align Python architecture strategies with long-term technology objectives. Innovation and R&D: - Stay updated with the latest advancements in Python, Agentic AI/LLM deployment frameworks, cloud-native backend tools, and data engineering patterns. - Drive innovation by prototyping modern Python frameworks and proposing execution upgrades. Budget & Resource Management: - Assist in infrastructure budgeting by estimating cloud resources, data storage requirements, and compute capacity. - Ensure designed solutions are cost-eff