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Senior Agentic AI Engineer - 2026 Roadmap

Aether Systems
San Francisco
Estimated Salary
USD 160.000 – USD 240.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

We are pioneering the Agentic AI Revolution for the year 2026 and beyond. As a Senior Agentic AI Engineer at Aether Systems, you will architect the next generation of autonomous intelligent agents capable of complex reasoning and self-improvement.

Your mission is to bridge the gap between cutting-edge Large Language Models (LLMs) and real-world application stability, ensuring our solutions are secure, scalable, and transformative.

Why Join Us?

  • Work on the Future of AI (2026 Vision).
  • Competitive salary and equity package.
  • Flexible remote-first culture with a San Francisco hub.

Responsibilities

  • Architect Agentic Workflows: Design and implement scalable, multi-agent systems that leverage LLMs for autonomous decision-making and task execution.
  • Model Optimization: Fine-tune open-source models (e.g., LLaMA, Mistral) and optimize inference pipelines for low latency and high throughput in production environments.
  • RAG Implementation: Develop advanced Retrieval-Augmented Generation architectures to enhance model accuracy and reduce hallucinations.
  • Safety & Alignment: Implement guardrails and safety protocols to ensure AI agents operate within ethical and regulatory boundaries.
  • MLOps & Deployment: Manage the end-to-end lifecycle of AI models using Docker, Kubernetes, and modern CI/CD pipelines.
  • Cross-Functional Collaboration: Partner with product managers and data scientists to translate complex requirements into robust engineering solutions.

Qualifications

  • Education: MS or PhD in Computer Science, Artificial Intelligence, or a related technical field.
  • Experience: 5+ years of professional experience in Deep Learning, NLP, or Generative AI.
  • Technical Skills: Strong proficiency in Python, PyTorch, or TensorFlow. Experience with LangChain or LlamaIndex is highly preferred.
  • Knowledge: Deep understanding of Transformer architectures, attention mechanisms, and prompt engineering techniques.
  • Deployment: Experience deploying ML models to cloud infrastructure (AWS, GCP, or Azure).
  • Soft Skills: Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow LLMs Generative AI RAG MLOps NLP Deep Learning Docker Kubernetes LangChain

Ready to Take This Challenge?

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