Job Description
Are you ready to architect the intelligence of tomorrow?
Nexus Future Labs is at the forefront of the 2026 AI revolution. We are building the next generation of autonomous systems—agents that don't just process data, but act, learn, and collaborate independently. We are looking for a visionary Senior Agentic AI Engineer to lead our core infrastructure team and define the standards for autonomous agent interaction.
If you are passionate about Large Language Models (LLMs), autonomous workflows, and building systems that scale, we want to meet you.
Responsibilities
- Architect Autonomous Workflows: Design and implement complex multi-agent systems that leverage LLMs to perform high-level reasoning and execution without human intervention.
- Optimize Inference & Latency: Build high-performance inference pipelines, utilizing techniques like quantization and model distillation to ensure real-time agent responsiveness.
- Build Persistent Memory Systems: Develop vector database architectures and retrieval-augmented generation (RAG) systems that allow agents to retain context and learn from interactions over time.
- Agent Orchestration: Implement orchestration layers (e.g., LangChain, AutoGen) to manage agent-to-agent communication, tool use, and safety guardrails.
- Collaborate with Product: Translate complex technical concepts into robust product features that delight enterprise clients.
- Ensure Safety & Alignment: Proactively identify and mitigate hallucinations, biases, and security vulnerabilities in autonomous agent behavior.
Qualifications
- Education: BS, MS, or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional software engineering experience, with at least 2 years specifically focused on AI/ML or Deep Learning.
- Technical Proficiency: Deep understanding of Python, PyTorch, or TensorFlow. Experience with fine-tuning LLMs (e.g., Llama 3, Mistral) is required.
- Framework Mastery: Strong hands-on experience with AI agent frameworks such as LangChain, Semantic Kernel, or AutoGen.
- System Design: Proven ability to design scalable microservices and distributed systems handling high throughput.
- Problem Solving: Exceptional ability to debug complex, multi-modal problems in dynamic environments.