• Develop and maintain Java applications • Collaborate with cross-functional teams • Involve in real-time project implementations • Utilize Kubernetes for container orchestration • Implement CI/CD strategies for deployment

• Desarrollar servicios backend utilizando Python y .NET/C# • Integrar marcos basados en LLM como LangGraph, AutoGen, etc. • Colaborar en flujos de trabajo impulsados por IA y arquitecturas escalables. • Construir frontends en React para aplicaciones impulsadas por IA.

• Sitting with product and client stakeholders to understand the real problem, then helping shape it into something concrete that can actually be built. • Owning features end to end, from early scoping and design through to building, testing and getting them live. • Using AI coding agents to move fast, while staying firmly in control of the quality, structure and long-term health of the code. • Building and integrating LLMs into features, refining the prompts, evaluations and guardrails that make AI-assisted features behave reliably in production. • Working against a defined data model and a clear contract, and flagging early when something doesn’t add up rather than building the wrong thing quickly. • Feeding what you learn back to the product and client teams, so each iteration is sharper than the last.

• Design, develop, and maintain Python-based backend microservices • Build and integrate REST APIs (authentication, RBAC, third-party integrations) • Contribute to real-time voice pipeline integrations (SIP / WebRTC / LiveKit) • Develop integrations with external systems (e.g., Zoho CRM, Google / Microsoft Calendar) • Deploy and operate services on AWS (ECS, CloudWatch, Secrets Manager, S3) • Maintain CI/CD pipelines using Bitbucket Pipelines • Containerize services using Docker / Docker Compose • Collaborate with AI, frontend, and DevOps teams; participate in code reviews and release processes