Senior LLM Engineer
hace 2 semanas
Job Description
Job Title:
Senior LLM Engineer
Job Type:
Full-time
Location:
Buenos Aires (Hybrid or Remote)
Experience:
4-6+ Years of Relevant Experience
Job Summary:
Join our team as a Senior LLM Engineer and play a pivotal role in designing, building, and optimizing next-generation Generative AI applications. You will leverage your expertise in Large Language Models, state-of-the-art AI platforms, and cloud technologies to deliver scalable, production-grade AI solutions. We value clear, impactful written and verbal communication as much as deep technical skill.
Responsibilities:
- Lead the architecture and implementation of GenAI systems — including RAG, multi-agent workflows, and autonomous reasoning frameworks.
- Architect and optimize complex data ingestion, embedding, and retrieval pipelines using vector databases.
- Build scalable, low-latency APIs and integrate LLM capabilities into production-grade platforms.
- Evaluate and select appropriate frameworks and tools (e.g., Neo4j vs. Neptune for graph data) based on project needs.
- Mentor junior engineers and drive best practices in system design and deployment.
- Oversee deployment architectures on AWS or Azure, ensuring reliability and cost efficiency.
- Innovate in emerging GenAI areas — multi-agent coordination, MCP, and agent-to-agent communication (A2A).
- Collaborate with leadership and cross-functional teams to align technical roadmaps with strategic goals.
Must-have Skills:
- Python
: Expert. Strong design, debugging, and optimization capabilities. - API Development
: Advanced knowledge of FastAPI or equivalent frameworks. - GenAI Stack
: LangChain, LangGraph, LangSmith, and hands-on with multiple LLMs. - RAG Expertise
: End-to-end lifecycle mastery — from data processing to deployment. - Architectural Thinking
: Tool comparison, scalability, fault tolerance, performance trade-offs. - Cloud/DevOps
: Deep hands-on experience with AWS or Azure (infrastructure, monitoring, CI/CD).
Good-to-have Skills:
- Emerging Tech
: MCP, A2A agents, advanced orchestration frameworks. - Responsible AI
: Experience applying governance and safety frameworks. - Leadership
: Mentorship, technical roadmap ownership, code review. - Cross-System Integration
: Familiarity with microservices, event-driven design, and messaging queues.
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