Forward Deployed AI Engineer
K
KeyrusAI Engineering
ColombiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5-10 years
- Required Skills
- DockerPythonGitCI/CDLLMMLOpsGenerative AILangChain
Requirements
- 5-10 years of experience in AI Engineering, Machine Learning, Software Engineering, Data Engineering, or technical consulting.
- Hands-on experience delivering AI, GenAI, or software solutions into production.
- Experience working directly with clients or in complex stakeholder environments.
- Strong Python development skills and experience with modern software-engineering practices.
- Experience with Large Language Models, GenAI architectures, and model/provider selection.
- Proficiency with RAG, embeddings, vector search, AI agents, and agentic workflows.
- Familiarity with frameworks such as LangChain, LlamaIndex, LangGraph, Semantic Kernel, or AutoGen.
- Experience integrating AI into enterprise systems and APIs.
- Working knowledge of major cloud platforms (Azure, AWS, or GCP).
- Familiarity with Docker, Git, CI/CD, and production deployment/monitoring.
- Understanding of MLOps/LLMOps, security, data privacy, and governance principles.
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).
Responsibilities
- Co-create solutions with business and technical stakeholders through workshops, rapid iterations, and hands-on delivery.
- Locate, qualify, and secure access to the data required for each use case.
- Translate use cases into production-ready GenAI and agentic AI solutions, including RAG architectures, intelligent assistants, and AI-enabled workflows.
- Prototype, test, deploy, monitor, and improve solutions in real client environments.
- Work with cross-functional teams including Data Engineers, Software Engineers, and Governance experts to deliver sustainable outcomes.
- Define success criteria including adoption, performance, reliability, risk, cost, and measurable business value.
- Ensure solutions are documented, governed, and transferable for client operation.
- Develop reusable patterns, accelerators, and building blocks to strengthen future engagements.
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