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Jobs(31,341)/Backend Engineer Role(675)/BriteCore (2) - Senior Python Backend Engineer
BriteCore

BriteCore - Senior Python Backend Engineer

Remote - São Paulo1mo ago
RemoteSeniorLATAMCloud ComputingArtificial IntelligenceBackend EngineerSenior Backend DeveloperPythonPostgreSQLMySQLSQLDjangoCursorReactAWSVue.jsDockerSlackClaude

Requirements

• Bachelor’s Degree or higher in Computer Science or a related field • 5+ years of experience in Python web development • 3+ years with SQL databases (e.g., MySQL, PostgreSQL) • 3+ years of SaaS product development, including cloud based solutions • 3+ years of hands on experience with Django or another Python framework • 2+ years of proven experience building and consuming APIs • Daily, deliberate use of agentic AI coding tools such as: Claude, Cursor, Codex • Proven ability to direct AI agents on multi file, long horizon tasks • Hands on experience with frontend frameworks like Vue.js or React • Professional experience working with Docker for containerization and AWS • Excellent verbal and written communication skills • 2+ years of experience working at a scaling startup • Experience with spec driven development: using AI to generate tests, scaffolding or architecture from requirements • Hands on experience building production AI agents or multi-step LLM pipelines using LangChain, LangGraph, or equivalent orchestration frameworks • Proven use of Agent Teams in Claude Code, multi agent orchestration via Codex, or similar parallel agentic workflows • This isn’t your typical AI generated job description • What did we do different? • Other companies: Basic AI • Us: Claude Cowork (Opus 4.7) • The same reason you’re still reading the job description • Here was our first prompt • I need to use Cowork to update a job description for a Senior Python Backend Engineer role. The current job description is in a folder on my desktop called "Job Description" • I want Cowork to pull from three Slack channels: #eng-general-int, #product-general-int and #ai-for-makers - plus any design docs from the last three months, to understand what we've actually been shipping. Then update the job description based on what it learns • Final output should be a Google Doc. Help me write the Cowork prompt • [Our recruiter wrote this prompt, not an engineer] • Life at BriteCore • We take pride in our dynamic, diverse team, unified by shared values of community, integrity, grit and impact. We love what we do and the people we do it with, which is why we welcome every individual, provide them with equal opportunity irrespective of their race, color, national origin, religion, age, gender identity, sexual orientation, veteran, disability or any other legally protected rights that one has. • Click here to learn more about our platform. • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Responsibilities

• Push production AI agents into the platform's most complex flows. Build the MCP servers that orchestrate them: tool layer, context handling, model routing through OpenRouter • Build the integration layer that powers the platform and the AI agents on top of it: identity, e-signature, real time data services. Every call has a user or an agent on the other end • Build the rules engines, configuration runtime, and AI Copilots that turn the platform into a product factory. Customers ship entirely new products without us touching the code • Bring whole companies onto the platform: importer pipelines, schema mapping, hard go-live dates. Every customer's data shape is different. Every cutover has a deadline that doesn't move • Engineer the multi-tenant infrastructure companies run on. Async workers, document pipelines, scheduled jobs touching every site. The AI agent fleet is joining them tenant by tenant • Design the public APIs the entire customer ecosystem runs on, with AI agents as first-class consumers and the contracts that let new endpoints ship at speed

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