Senior Python Developer

Description

Job Summary: We are seeking a Senior Python Developer to design, build, and operate Chatbot solutions for a corporate GENAI using advanced RAG techniques and continuous integration with agent frameworks, contributing to architecture, best practices in evaluation/observability, and security hardening. Key Highlights: 1. Design, build, and operate Chatbot solutions for corporate GENAI 2. Apply advanced RAG techniques and integrate with agent frameworks 3. Support architecture, evaluation/observability, and security (LGPD) Description: About the Role We are looking for a Senior Python Developer to design, build, and operate Chatbot solutions for a corporate GENAI using advanced RAG techniques and continuous integration with agent frameworks. You will contribute to architecture, best practices in evaluation/observability, and security hardening (LGPD), using LangChain/LangGraph, LlamaIndex, FlowiseAI, AGNO, and CrewAI. Responsibilities* Maintain and design new RAG pipelines (ingestion, chunking, embeddings, retrievers, re\-ranking, synthesis). * Design \*\*agents\*\* — both single-agent and multi\-agent — with flow control (state machines/DAGs) and external tools. * Evolve architecture, testing, and observability (tracing, metrics, cost, reliability). * Integrate data sources (PDF/HTML/DB/S3\), vector stores, and hybrid search (BM25 \+ semantic). * Build secure tools (auth, rate limits, PII masking) and guardrails. * Define SLIs/SLOs jointly with Product/Security teams and mentor less experienced team members. Required Qualifications* Advanced Python (typing, Pydantic/dataclasses, \`asyncio\`, pytest, logging). * Hands\-on RAG experience with LangChain/LangGraph and LlamaIndex (retrievers, query engines/routers). * Experience with multi\-agent systems using CrewAI and/or AGNO (roles, memory, delegation, routing). * Practical experience with FlowiseAI (building flows, integrating via API/Custom Nodes). * Vector databases: pgvector, FAISS, or Chroma; (Pinecone/Weaviate is a plus). * Hybrid search: Elasticsearch/OpenSearch (BM25 \+ kNN/vector). * Re\-ranking (Cohere) and evaluation (groundedness/faithfulness, prompt testing). * Observability: Langfuse, Openlayer, and/or OpenTelemetry. * Basic DevOps: Docker, CI/CD; familiarity with Kubernetes. * LGPD compliance, PII masking, and collection/index\-level access control. * Technical reading proficiency in English. Interpersonal Skills* Clear and empathetic communication: contextualize decisions, adapt language to audience, and validate understanding. * Ownership without ego: take end\-to\-end responsibility, share credit, and learn from mistakes. * Collaborative mentoring: PRs that teach, pairing when valuable, rapid unblocking of the team. * Product/business focus: connect technical work to impact (SLIs/SLOs, cost, timeline) and negotiate trade\-offs. * Healthy conflict and documented decisions: debate with data, justify and test hypotheses, and document (ADRs). * Operational discipline: predictability (status/risks), testing, observability, and minimal documentation. * Adaptability: adjust plans based on new facts, share learnings, and recognize that pivoting is necessary when well\-founded. * Awareness of quality, security, and ethics: consider sensitive data and reliability before writing code. * Responsible asynchronous work: document decisions clearly, ensure smooth handoffs, respect time zones or occasional delays from internal or external dependencies. * Emotional maturity: remain calm under pressure, welcome feedback, and separate people from problems. Nice\-to\-have* Advanced LangGraph (recovery/branching/retries) or production use of LlamaIndex Workflows/Agents. * Asynchronous pipelines (Celery/RQ), OCR, and robust parsing (PDF/image/video). * Enterprise integrations (MCP, Azure/O365\) for agent\-driven office platform automation. Job Details* Hybrid work model * PJ contract Benefits* 30 days of paid leave * Totalpass * Well\-being program * Telemedicine service * Benefits clubs * Birthday day\-off 2512050202181824779