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Senior AI Engineer: Agentic Systems (2026 Focus)

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Are you ready to architect the intelligent systems that will define the future of work in 2026? Nexus Future Labs is seeking a visionary Senior AI Engineer to lead our charge into the era of Agentic AI. In this pivotal role, you will not just be deploying models; you will be building autonomous ecosystems capable of complex reasoning, self-correction, and goal-oriented execution.

We are looking for a technical leader who thrives at the intersection of deep learning, distributed systems, and product innovation. If you want to be at the forefront of the AI revolution, shaping the standards for autonomous agents in the 2026 landscape, we want to hear from you.

Responsibilities

  • Architect Autonomous Agents: Design and implement advanced AI agents using Large Language Models (LLMs) and Reinforcement Learning to perform complex, multi-step tasks autonomously.
  • Optimize Inference Pipelines: Engineer high-performance inference systems to ensure low latency and cost-efficiency at scale.
  • Build RAG Architectures: Develop robust Retrieval-Augmented Generation (RAG) systems to ground AI agents in enterprise knowledge bases.
  • System Design: Lead the design of scalable microservices and backend infrastructure using cloud-native technologies (AWS/GCP).
  • Safety & Alignment: Implement guardrails and safety protocols to ensure agent behavior remains ethical and aligned with human intent.

Qualifications

  • Education: Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
  • Core Tech: Deep expertise in Python, PyTorch, and modern Machine Learning frameworks.
  • Experience: 5+ years of experience in software engineering with a focus on AI/ML.
  • LLM Mastery: Proven track record of building and deploying LLM applications (LangChain, LlamaIndex, OpenAI API).
  • Distributed Systems: Strong understanding of distributed computing, message queues, and containerization (Docker, Kubernetes).
  • Problem Solving: Ability to tackle ambiguous problems and design systems for the 2026 tech stack.

Required Skills

Python PyTorch LLM Agentic AI RAG Kubernetes Docker AWS Machine Learning Natural Language Processing

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