Descripción de la oferta
Duración de la oferta: hasta el 25/10/2025.
Funciones
– Build and Integrate AI Solutions using LLM APIs (OpenAI, AWS Bedrock, Anthropic, Mistral) — not just plan, but hands-on develop.
– Shape LLM behavior through prompt engineering, guardrail development, and fine-tuning pipelines.
– Design and build scalable APIs (e.g., FastAPI , Flask) to enable AI-driven features across products.
– Lead performance tuning and ensure system scalability across mobile and cloud platforms.
– Implement GenAI Safety Best Practices , focusing on hallucination mitigation and secure model usage.
– Estimate and optimize costs for large-scale cloud LLM operations
– Consult and Communicate AI strategies to legal, compliance, quality, and executive teams — tailoring technical concepts to diverse audiences.
– Own and Drive Tactical Execution of AI initiatives across multiple products, not just providing oversight.
Requisitos
– Bachelor's Degree with 10+ years of experience or Master's Degree with 7+ years of related software architecture experience (not all AI related) across mobile and cloud platforms.
– 4–8 years of hands-on experience developing and implementing AI/LLM architecture and solutions. (Flexibility on years given AI’s rapid evolution .)
– Strong Python development skills— building new APIs, integrating LLMs, and engineering GenAI applications.
– Deep experience working with cloud-based LLMs (e.g., OpenAI, AWS Bedrock, Anthropic, Mistral models).
– Testing and Debugging — p roficiency in AI app testing techniques, including unit testing, integration testing, and UI testing across various mobile devices and operating system platforms.
– Strong communication and documentation skills — producing diagrams, demos, and technical artifacts that make AI strategies understandable and actionable.
– Proven ability to design for cost efficiency and scalability.
– Strategic thinker who balances technical innovation with business needs.
Preferred Qualifications
– Experience developing GenAI agents and LLM meshes.
– Background in large enterprise architecture or scaling AI solutions across multiple business units.
– Experience working in or around regulated industries (healthcare, life sciences, finance) is a plus.
