Sr AI Engineer

nimblegravity; United States; Hybrid; USD 130,000 - 180,000; Full time

Benefits offered by this job

Job summary

nimblegravity is seeking a Data & AI practitioner to design and deploy generative AI solutions for clients across industries in the United States.

You will turn cutting-edge LLM, RAG, and multimodal techniques into reliable production systems, collaborating with engineering, product, and data teams to deliver high‑impact AI outcomes.

You'll work with LangChain, LangGraph, Hugging Face, PyTorch, MCP, and multi‑agent frameworks on Azure, AWS, or Databricks to build scalable AI apps.

Qualifications

• Hands-on experience with production-scale AI/ML systems.
• Strong Python and ML framework knowledge.
• Experience on cloud/data platforms (Azure/AWS/GCP/Databricks).
• Experience with structured and unstructured data processing.

Responsibilities

• Design, build, and deploy AI solutions using LLMs, RAG, embeddings, vector databases, and agents.
• Develop intelligent systems that process documents, retrieve knowledge, and automate workflows.
• Work with LangChain, LangGraph, Hugging Face, PyTorch, MCP, and multi-agent frameworks.
• Build scalable AI applications across Azure, AWS, Databricks, or similar platforms.
• Experiment with foundation models, prompts, and orchestration patterns.
• Partner with engineering, product, data, and business stakeholders to deliver high-impact AI outcomes.

Skills

AI engineering

Python

Cloud platforms

Communication

Education

Advanced degree in CS/AI

Tools

LangChain

LangGraph

Hugging Face

PyTorch

MCP

Job description

Role overview

Join a Data and AI practice designing and deploying advanced generative AI solutions for clients across industries. The role focuses on turning cutting‑edge LLM, RAG, agent, and multimodal techniques into reliable production systems, while staying plugged into a fast‑moving ecosystem and bringing emerging ideas into real client work.

Responsibilities

• Design, build, and deploy AI solutions using LLMs, RAG, embeddings, vector databases, semantic search, and agentic architectures.
• Develop intelligent systems that process documents, retrieve knowledge, generate content, automate workflows, and convert unstructured data into actionable insights.
• Work with modern GenAI and AI engineering tools such as LangChain, LangGraph, Hugging Face, PyTorch, MCP, and multi‑agent frameworks, alongside cloud‑native AI services.
• Build scalable, reliable AI applications across Azure, AWS, Databricks, or comparable cloud and data platforms.
• Experiment with and evaluate foundation models, prompts, retrieval strategies, orchestration patterns, and performance optimization techniques.
• Partner with engineering, product, data, and business stakeholders to define technical approaches and deliver high‑impact AI outcomes.

Requirements

• Strong experience in AI, machine learning, data science, or AI engineering, with hands‑on exposure to production‑scale solutions.
• Deep practical experience with Generative AI, including LLMs, RAG, vector search, embeddings, agents, and AI workflow orchestration.
• Strong Python skills with modern ML and 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.
• Comfort working with structured and unstructured data, including text, documents, images, emails, and spreadsheets.
• Builder mindset with 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.

Benefits and work setup

• Open to candidates based in LATAM or the United States. Equal opportunity employer committed to evaluating all qualified applicants without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under applicable law.