Senior AI (Generative, MLOps)

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Create intricate AI architectures that encompass the entire solution lifecycle, from initial design to operational deployment.

• Serve as a technical expert, guiding architectural choices and advocating for best practices in AI engineering.

• Develop and implement Generative AI solutions utilizing LLMs and Retrieval-Augmented Generation (RAG) to tackle significant enterprise challenges.

• Define and enhance a comprehensive MLOps ecosystem that includes training, versioning, deployment, and monitoring.

• Set governance, security, and ethical AI standards, which encompass access control, safeguarding sensitive data, and conducting model risk assessments.

• Guarantee scalability, resilience, and cost-effectiveness of AI solutions in a production environment.

• Establish model evaluation strategies that incorporate both technical and business-oriented metrics.

• Evaluate emerging technologies and suggest pathways for their adoption, weighing innovation against practicality.

• Convert business challenges into AI architectures by collaborating closely with both technical teams and executive stakeholders.

⛳️ Requirements

• Demonstrated experience in AI engineering with a proven history of designing complex architectures.

• Expertise in the complete AI solution lifecycle, from design and experimentation to operational deployment.

• Extensive experience with Generative AI, particularly LLMs and RAG architectures in production.

• Familiarity with large-scale MLOps ecosystems that cover training, versioning, deployment, and monitoring.

• Practical experience with AWS AI and Machine Learning services, including SageMaker and Bedrock.

• Proficient in Python for developing AI and Machine Learning solutions.

• Understanding of SQL and data handling for preparing datasets.

• In-depth knowledge of AI governance, security, and ethical use, including the protection of sensitive data and assessment of model risks.

• Experience in ensuring the scalability, resilience, and cost-effectiveness of production AI solutions.

• Capability to act as a technical reference, leading architectural decisions and mentoring peers.

• Differentiators: experience with LangChain, LangGraph, CrewAI, or similar tools; knowledge of vector databases; advanced retrieval and evaluation strategies for RAG; familiarity with PyTorch or TensorFlow; experience with Docker and Kubernetes; understanding of Terraform or CloudFormation; AWS certifications; and experience in consulting or serving multiple clients.

• Possess technical leadership presence, strategic vision, critical thinking skills, clear communication abilities, sound judgment regarding AI risks, independence, and technical inquisitiveness.

🏝️ Benefits

• Continuous training and professional development opportunities.

• A motivating work environment and culture.

• Fully remote work flexibility.

• Position is also open to candidates with disabilities (People with Disabilities - PwD).