The job, in the employer's words
Sr AI Engineer – Generative AI & Agentic Systems
We’re looking for an exceptional Sr AI Engineer to join our growing Data & AI practice and help build the next generation of AI-powered solutions.
This role is ideal for someone who loves working at the edge of what’s possible with LLMs, RAG, agents, semantic search, multimodal AI, and intelligent automation — and who wants to turn cutting-edge ideas into real, production-ready systems for clients across industries.
This position is open to candidates based in LATAM or the United States.
What You’ll Do
- Design, build, and deploy advanced AI solutions using LLMs, RAG, embeddings, vector databases, semantic search, and agentic architectures.
- Develop intelligent systems that can process documents, retrieve knowledge, generate content, automate workflows, and transform unstructured data into actionable insights.
- Work with modern GenAI and AI engineering tools such as LangChain, LangGraph, Hugging Face, PyTorch, MCP, multi-agent frameworks, and cloud-native AI services.
- Build scalable, reliable AI applications across Azure, AWS, Databricks, or similar cloud/data platforms.
- Experiment with and evaluate foundation models, prompts, retrieval strategies, orchestration patterns, and performance optimization techniques.
- Collaborate closely with engineering, product, data, and business teams to define the right technical approach and deliver high-impact AI solutions.
- Stay plugged into the fast-moving GenAI ecosystem and bring new ideas, tools, and prototypes into real-world applications.
What You Bring
- 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.
- A 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 the ability to partner with technical and non-technical stakeholders.
Nice to Have
- Advanced degree in Computer Science, Data Science, AI, Machine Learning, or a related technical field.
- Experience with MCP, multi-agent systems, fine-tuning, LLM evaluation frameworks, multimodal AI, or production ML observability.
- Prior consulting, client-facing, or cross-functional delivery experience.
About Nimble Gravity
Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization.
Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.
Requirements mentioned
- 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.
- A 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 the ability to partner with technical and non-technical stakeholders.
- Advanced degree in Computer Science, Data Science, AI, Machine Learning, or a related technical field.
- Experience with MCP, multi-agent systems, fine-tuning, LLM evaluation frameworks, multimodal AI, or production ML observability.
- Prior consulting, client-facing, or cross-functional delivery experience.
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