Sr AI Engineer
Salary not listed • Remote • LATAM (Remote), US (Remote) • Full-time
Posted 5mo ago
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Job Location
LATAM (Remote), US (Remote)
Tech Stack
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
AI Engineer
About the job
We are seeking an exceptional Senior AI Engineer to join our Data & AI practice and contribute to building the next generation of AI-powered solutions. This role is perfect for individuals passionate about exploring the frontiers of LLMs, RAG, agents, semantic search, multimodal AI, and intelligent automation, with a desire to transform cutting-edge concepts into production-ready systems for diverse clients. The position is open to candidates located in LATAM or the United States.
Responsibilities
- Design, build, and deploy advanced AI solutions using LLMs, RAG, embeddings, vector databases, semantic search, and agentic architectures.
- Develop intelligent systems for document processing, knowledge retrieval, content generation, workflow automation, and transforming unstructured data into insights.
- Utilize modern GenAI and AI engineering tools like LangChain, LangGraph, Hugging Face, PyTorch, MCP, multi-agent frameworks, and cloud-native AI services.
- Build scalable and reliable AI applications on cloud platforms such as Azure, AWS, Databricks, or similar.
- Experiment with and evaluate foundation models, prompts, retrieval strategies, orchestration patterns, and performance optimization techniques.
- Collaborate with engineering, product, data, and business teams to define technical approaches and deliver high-impact AI solutions.
- Stay current with the GenAI ecosystem and integrate new ideas, tools, and prototypes into real-world applications.
Requirements
- Strong experience in AI, machine learning, data science, or AI engineering with hands-on exposure to production-scale solutions.
- Deep interest and practical experience with Generative AI, including LLMs, RAG, vector search, embeddings, agents, and AI workflow orchestration.
- Strong Python skills and experience with modern ML/AI frameworks and libraries.
- Experience building on cloud or data platforms such as Azure, AWS, GCP, Databricks, or similar.
- Solid foundation in data science, experimentation, statistical thinking, or applied machine learning.
- Ability to work with structured and unstructured data, including text, documents, images, emails, spreadsheets, or other complex data formats.
- A builder mindset: curious, hands-on, adaptable, and excited to work with emerging technologies.
- Strong communication skills and ability to partner with technical and non-technical stakeholders.