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Remote in Argentina, & 2 others
Python.Core& 8 others
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We are building a Chief Python Developer role to set technical direction and lead hands-on delivery for backend AI services and LLM orchestration. You will write production Python, mentor engineers, and collaborate with Security, Data, and Infrastructure while aligning with US-based product and engineering partners. Help raise observability, reliability, and operational excellence across pod services—apply now.
Responsibilities
- Define technical direction for the pod and own architecture decisions within scope
- Deliver production code (~50%+ of the time) across backend AI services, LLM orchestration and frontend integration
- Design and build Agentic Experiences (AX) with streaming, low-latency agent UIs
- Coach 3 Senior Engineers and 1 Data Engineer within the pod
- Collaborate daily with Security, Data and Infrastructure teams
- Coordinate with US-based product and engineering counterparts
- Run design reviews and remove blockers to protect sprint deliverables
- Uphold observability, SLOs and reliability standards for pod services
Requirements
- Proven track record with 7+ years of software engineering experience owning complex backend systems end-to-end
- Hands-on experience of 3+ years with LLM-era AI/ML platforms such as LangChain, LangGraph or Bedrock in production; deeper pre-LLM ML backgrounds (TensorFlow, scikit-learn) with a clear recent pivot to generative AI are also considered
- Expert-level proficiency in Python for backend services and AI integration as the primary language for backend and AI work
- Deep expertise in LangChain, LangGraph and LangSmith to orchestrate multi-step, multi-agent workflows plus evaluation/observability
- Solid background running production workloads with AWS, Docker and microservices
- Practical skills with GitHub Actions, ArgoCD and OpenTofu/Terraform
- Strong understanding of secure coding practices, auth/authz awareness and data governance as default standards
- Advanced knowledge of API design including RESTful APIs and microservices
- English proficiency at B2 (Upper-Intermediate) level or higher
Nice to have
- Fluency in React and TypeScript with ability to contribute to UI-layer code and review frontend work
- Familiarity with MCP (Model Context Protocol) and emerging agent interoperability standards
- Knowledge of AI evaluation tooling such as RAGAS or custom eval frameworks
- Background designing and optimizing RAG pipelines with vector databases (Amazon Kendra, OpenSearch)
- Understanding of identity/security domains (IAM, CIAM) and working with unstructured data (images, videos) using prompt context management via LangGraph State