Enterprise AI Solutions Engineer - RAG & Agent Systems

Mission.dev; Northern (KY); On-site; USD 175,000 - 200,000; Full time

Job summary

Mission.dev is seeking an experienced AI Engineer to design and deliver production-grade AI applications for enterprise clients in LATAM, reporting to regional leadership. You will own end-to-end AI projects, from architecting intelligent agent systems to implementing RAG pipelines and ensuring scalable, reliable deployments.

The role emphasizes deep technical engagement with customers, cross-functional collaboration, and mentoring on building client applications using Python and modern AI

Qualifications

• 5+ years of backend systems development and recent AI/ML experience.
• Hands-on expertise with LLM platforms and agentic frameworks such as LangChain, LangGraph, or CrewAI.
• Advanced proficiency in Python and experience building scalable backend services or APIs.
• Practical experience with vector databases like Pinecone, Weaviate, or FAISS.

Responsibilities

• Translate complex business requirements into production-ready AI solutions through direct customer engagement.
• Architect and integrate intelligent multi-step agent systems to automate enterprise functions.
• Develop retrieval-augmented generation pipelines to contextualize model behavior with client data.
• Collaborate with cross-functional teams to ensure seamless platform integration.
• Oversee the full AI project lifecycle from data prep to deployment and monitoring.
• Provide product feedback and mentor clients on building their own applications.
• Maintain clean, scalable Python code and best practices for system performance.

Skills

Weaviate

Pinecone

LangGraph

CrewAI

Python

LLM platforms

Agentic frameworks

Tools

LangChain

LangGraph

CrewAI

Job description

Mission.dev is seeking an experienced AI Engineer to design and deliver production-grade AI applications for enterprise clients in LATAM, reporting to regional leadership. You will own end-to-end AI projects, from architecting intelligent agent systems to implementing RAG pipelines and ensuring scalable, reliable deployments.

The role emphasizes deep technical engagement with customers, cross-functional collaboration, and mentoring on building client applications using Python and modern AI