Role Description - Design, develop, and maintain ESB integration solutions. - Develop and support APIs, web services, and enterprise integrations. - Build and maintain REST and SOAP services. - Integrate enterprise applications, databases, and third-party systems. - Troubleshoot and resolve integration-related issues. - Perform unit testing, system integration testing, and production support. - Collaborate with Business Analysts, Solution Architects, and Development teams to gather integration requirements. - Ensure integration solutions follow security, scalability, and performance best practices. - Prepare technical documentation and integration specifications. - Participate in code reviews and technical design sessions. Qualifications - 5+ years of related experience developing and implementing solutions using Middleware. - In-depth working experience developing applications using different programming languages used in ESB. - In-depth knowledge of standards/technologies (JMS, XML, JSON, WSDL, SOAP, REST, HTTP, and SSL/TLS). - Experience with different types of Integration Patterns. - Sound knowledge of OOP. - Good knowledge of multiple mapping tools. - Stakeholder communication by translating complex technical integration concepts into clear, actionable business insights, and vice versa. Requirements - Define integration test scenarios, facilitate User Acceptance Testing (UAT), and help validate that integrated systems meet business and data integrity standards. - Work alongside Integration Engineers to define API contracts, payload structures (JSON/XML), and endpoints using tools like Postman or Swagger/OpenAPI.

• Design, build, and deploy end-to-end AI and machine learning solutions, with a focus on GenAI, NLP, and healthcare applications. • Develop and productionize LLM-based workflows, including prompt engineering, evaluation frameworks, fine-tuning approaches, and Retrieval-Augmented Generation systems. • Translate ambiguous business and healthcare problems into structured data science solutions with clear success metrics. • Own the full model lifecycle, including data preparation, experimentation, validation, documentation and articulation of results, deployment, monitoring, and continuous improvement following RAI guidelines. • Work with large-scale structured and unstructured data, including clinical, operational, claims, member, provider, or other healthcare-related datasets. • Partner with product, engineering, business, clinical, and compliance stakeholders to ensure solutions are scalable, explainable, secure, and aligned with business needs. • Lead, mentor, and develop a team of data scientists, and AI engineers, setting high standards for technical quality, analytical rigor, and delivery discipline. • Drive best practices in model development, code quality, documentation, reproducibility, and responsible AI.

• Lead end-to-end architecture for data platforms and pipelines: scraping, data extraction, transformation, storage, serving, and ML/LLM integration, balancing performance, reliability, security, and cost. • Incrementally scale pipelines and systems: design safe rollout plans and north star data-quality metrics to handle customer and traffic growth without impacting production. • Translate business goals into actionable data products: assess high-level requirements, carve clear problem spaces, draft crisp RFCs, and sequence work into deliverable projects for the team. • Establish and enforce engineering standards: testing strategy, evals, observability, data contracts, and security practices across services. Think through short-term and long-term goals to come up with fast go-to-market products, while planning ahead for productization. • Up‑level the org: lead architecture reviews, codify patterns, mentor Senior Engineers, and multiply impact through documentation, code reviews, and pairing. • Startup‑ready: flexible, comfortable with ambiguity and constant change; proactive about process, documentation, and reliability without over‑engineering. • Lead the collaboration and define how AI engineers work cross-functionally with software engineers, devops, product managers and designers, to conceptualize and shape innovative and impactful solutions. Provide mentorship to junior team members and cultivate a culture of collaboration and innovation. • Ship meaningful experiments: prototype data/ML capabilities, evaluate feasibility and ROI, and make pragmatic calls on productionalizing with an eye on operating costs and risk.

Role Description ¿Buscas una forma flexible de generar ingresos extra? Estamos invitando personas a participar en un proyecto de entrenamiento de IA grabando actividades reales de su día a día desde casa. Graba cuando quieras, utilizando tu propio dispositivo, mientras realizas actividades cotidianas como cocinar, limpiar, organizar espacios o realizar tareas domésticas. Qualifications - Sin experiencia previa Requirements - iPhone 16/17, Google Pixel 6+ o Samsung Galaxy S21+ o superior - Nivel básico de inglés - Acceso a internet Benefits - Trabajo remoto y flexible - USD $5 por hora de contenido aprobado - Bono por la primera hora aprobada