Job Description
We are seeking a visionary Agentic AI Engineer to architect the autonomous systems of 2026. At FutureScale Systems, we are building the neural infrastructure for the next generation of intelligent agents that can reason, plan, and execute complex tasks independently.
In this role, you will bridge the gap between cutting-edge LLM research and production-grade autonomy. You will design self-healing architectures, implement multi-agent orchestration frameworks, and push the boundaries of what is possible with autonomous decision-making.
Responsibilities
- Design and Deploy: Build scalable multi-agent systems using LangChain and AutoGen that can operate autonomously in dynamic environments.
- Reasoning Engines: Develop advanced Chain-of-Thought (CoT) and Tree-of-Thought (ToT) reasoning modules to improve agent reliability.
- Memory Systems: Implement sophisticated long-term and short-term memory architectures to allow agents to learn and adapt over time.
- Optimization: Optimize inference latency and cost using quantization and efficient serving techniques.
- Collaboration: Work closely with product and engineering teams to define the roadmap for 2026 autonomous capabilities.
Qualifications
- Experience: 5+ years of experience in Python, PyTorch, and deep learning frameworks.
- AI Mastery: Strong understanding of LLMs (GPT-4, Llama 3), RAG pipelines, and prompt engineering.
- Architecture: Proven ability to design distributed systems and microservices architectures.
- Education: MS or PhD in Computer Science, AI, or a related technical field.
- Tools: Familiarity with Vector DBs (Pinecone, Milvus) and orchestration tools.