gt-hq - Staff Architect / Tech Lead | NDA
Requirements
• Experience working in consulting, enterprise platform, or internal product environments • Experience using AI-assisted development tools such as Cursor, Claude, Codex, or similar • Excellent communication and stakeholder management skills • Strong problem-solving and decision-making abilities • Ability to thrive in ambiguous and fast-moving environments • Strong ownership mindset and accountability • Collaborative approach with the confidence to challenge ideas constructively • Ability to translate complex business requirements into scalable technical solutions • Experience working with cross-functional teams and senior stakeholders • INTERVIEW STEPS • 1. GT interview with Recruiter • 2. Technical interview • 3. Final interview
Responsibilities
• Define and own architecture for a new AI/Data product workstream • Design scalable backend services, data flows, and integration patterns • Guide implementation and support engineers through technical leadership • Review code, architecture decisions, and engineering standards • Collaborate with product stakeholders to translate requirements into technical solutions • Design and evolve data platform components, pipelines, and services • Contribute to AI-enabled product capabilities and agent-based workflows • Drive engineering quality, documentation, testing standards, and maintainability • Participate in hands-on implementation of complex technical initiatives • ESSENTIAL KNOWLEDGE, SKILLS & EXPERIENCE: • 8+ years of software engineering experience, including at least 2 years operating at Staff Engineer, Staff Architect, Principal Engineer, or Technical Lead level • Strong Python experience, ideally with FastAPI or similar backend frameworks • Strong system design and software architecture background • Experience building data platforms, ETL pipelines, or large-scale data systems • Experience with Databricks and modern data engineering practices • Experience working with cloud-native architectures (Azure, AWS, or GCP) • Familiarity with containerized environments (Docker) • Understanding of AI/LLM-enabled products and agent-based systems • At least Upper-Intermediate (B2+) English or higher • Experience building AI agent solutions in production
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