• Own and drive technical initiatives • Mentor mid-level and junior engineers • Build and maintain production systems • Shape how we work by contributing to architecture decisions

• Own and drive technical initiatives • Lead the architecture and delivery of major features across mobile, web, and API layers, from design through production • Make architectural decisions (service boundaries, data modeling, API contracts) and document them so the team can build on them • Elevate the team around you • Mentor mid-level and junior engineers through pairing, code review, and design discussions. Not just catching bugs, but teaching patterns • Transfer knowledge proactively, mentoring engineers to discover the "why" with a deep foundation of how systems are built • Establish and maintain coding standards, testing strategies for your initiative area • Build and maintain production systems • Design and build gRPC APIs using NestJS • Work across React Native (mobile) and React (web) to deliver cohesive member experiences • Define and implement service communication patterns using Protocol Buffers and gRPC • Own observability for your systems. Maintain Datadog monitors, Sentry error tracking, and know when something is wrong before users report it • Shape how we work • Contribute to architecture decisions in cross-team forums • Drive AI-native development practices by establishing workflows, sharing findings, and helping the team use AI tools effectively • Identify and raise risks early, including timeline slippage, technical debt, vendor reliability issues, and compliance gaps • Coordinate across team boundaries when your work touches other services or teams

• Work on implementation projects, supporting technical configuration and validation of integrations according to the client's environment • Backend development using Java and Android • Creation and optimization of queries in Oracle databases • Analysis and resolution of technical issues in development and production environments • Application of development best practices (Clean Code and SOLID principles) • Active participation in agile ceremonies (Scrum and Kanban)

• Lead the engineering strategy for AI solutions and platform (architecture, patterns, technical roadmaps and adoption guides). • Define and maintain standards and best practices for the development, testing and operation of AI applications (APIs, SDKs, templates, libraries and accelerators). • Monitor and drive the technical evolution of teams (architecture/code reviews, decisions and trade-offs). • Work on solving complex problems in distributed environments. • Serve as the technical reference in engineering applied to AI: model serving, integration with LLMs, RAG, data/feature pipelines, governance and security. • Track and evolve engineering and AI metrics, such as: SLO/SLI, latency, error rate, cost per request, response quality, hallucination, groundedness, test coverage and incident rate. • Collaborate in the design and development of platform tools and services with a focus on security, performance and observability (logs/metrics/traces, distributed tracing, end-to-end correlation). • Ensure operation and sustainment in production: monitoring and alerts, participation in war rooms, post-incident (RCA), continuous improvements and risk management. • Ensure scalability, resilience and consistency of AI solutions: rate limiting, fallback/degradation, caching, prompt/model versioning, data security and guardrails. • Continuously contribute ideas and proposals to enrich the roadmap (cost/latency reduction, quality improvement, evaluation automation, standardization of integrations).