AI Engineer (AI-Native)

LLMS, LLC
United States
21 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Computer Programming Python (Programming Language) Machine Learning Open Source Technology Search Technologies Software Engineering TypeScript Large Language Models Multi-Agent Systems Model Validation
+3 more
Build Management Kubernetes Machine Learning Operations

Job description

We’re looking for a Senior AI Engineer who doesn’t just work with AI, they think in it. This is a role for someone who has internalized AI-first development patterns, builds with LLMs as a primary primitive, and can architect systems that put intelligent automation at the core rather than the edge.

What You’ll Do

  • Design and build production-grade AI systems including LLM-powered pipelines, agentic workflows, and retrieval-augmented generation (RAG) architectures
  • Lead the integration of AI capabilities across products, from prototyping through to scalable deployment
  • Evaluate, fine-tune, and optimize foundation models for specific use cases; stay current on the rapidly evolving model landscape
  • Define engineering best practices for prompt engineering, model evaluation, observability, and safety guardrails
  • Collaborate with product and platform teams to identify high-leverage AI opportunities
  • Mentor engineers on AI-native development patterns and help level up the broader team

Requirements

  • 5+ years of software engineering experience, with at least 2 years focused on applied AI/ML systems
  • Deep hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and orchestration frameworks such as LangChain, LlamaIndex, or similar
  • Strong programming skills in Python, TypeScript, or equivalent, we care more about engineering fundamentals than language loyalty
  • Experience with vector databases (Pinecone, Weaviate, pgvector), embeddings, and semantic search
  • Proven ability to ship AI features to production, not just demos or notebooks
  • Comfort operating in ambiguity: you can take a vague idea and turn it into a scoped, working system
  • Experience with evaluation frameworks, A/B testing for model outputs, and monitoring for model drift or degradation

Nice to Have

  • Experience with fine-tuning or RLHF workflows
  • Familiarity with multi-agent architectures and tool-use patterns
  • Background in ML engineering (training pipelines, model serving, MLOps)
  • Contributions to open-source AI projects

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on app.dover.com

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