Job Description
We are seeking a visionary AI Agents Architect to lead the development of next-generation autonomous systems. As we prepare for the technological landscape of 2026, our team is building the backbone of a self-sustaining digital workforce. This is a rare opportunity to define how artificial intelligence interacts with enterprise workflows.
In this role, you will not just use AI; you will architect the very intelligence that drives it. You will work at the intersection of machine learning, distributed systems, and product innovation to create agents capable of complex reasoning, memory retention, and autonomous execution.
Responsibilities
- Architect Design: Design and implement scalable multi-agent systems using frameworks like LangChain, AutoGen, and custom orchestration layers.
- Performance Optimization: Optimize LLM inference pipelines and vector database queries to ensure sub-second latency and high throughput.
- Context Management: Develop sophisticated memory mechanisms and context windows to enable agents to maintain long-term dialogue and memory.
- Workflow Automation: Define and build agentic workflows that autonomously handle complex, multi-step business processes without human intervention.
- RAG Implementation: Spearhead the deployment of Retrieval-Augmented Generation architectures to ground agent responses in verified data sources.
- Ethical AI: Implement safety guardrails, hallucination detection, and ethical compliance checks within autonomous agent loops.
Qualifications
- Experience: 5+ years of software engineering experience, with at least 2 years dedicated to AI/ML or LLM application development.
- Technical Skills: Deep proficiency in Python, modern backend technologies (Node.js, Go), and cloud infrastructure (AWS/GCP).
- LLM Expertise: Extensive knowledge of Large Language Models (GPT-4, Claude, Llama 3) and experience fine-tuning models for specific domains.
- Data Engineering: Strong experience with vector databases (Pinecone, Milvus, Weaviate) and data ingestion pipelines.
- System Design: Strong understanding of distributed systems, API design (REST/GraphQL), and microservices architecture.
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.