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Generative AI Agent Architect

We’re looking for a forward‑thinking Generative AI Agent Architect to design and implement advanced, collaborative agent frameworks that power next‑generation applications. You will lead efforts to define, build, and orchestrate fleets of intelligent agents—leveraging LangChain, LangGraph, and crew‑based architectures—to solve complex business problems and deliver high‑velocity innovation. Key Responsibilities Agent Framework Design: Architect end‑to‑end agent pipelines using LangChain and LangGraph, defining clear interfaces, data flows, and orchestration patterns. Multi‑Agent Collaboration: Build and coordinate “agent crews” that work in parallel or series—delegating tasks, sharing context, and resolving conflicts to achieve a unified goal. Core Agent Development: Implement custom agents for retrieval, reasoning, planning, execution, and user interaction, fine‑tuning LLMs and embedding models as needed. Crew Orchestration: Design supervisory “master” agents and interaction protocols (queues, event buses, or graph triggers) to synchronize agent teams in real time. Infrastructure & DevOps: Containerize agent services (Docker/Kubernetes), set up CI/CD pipelines for model and code deployments, and integrate automated testing for agent behaviors. Scalability & Monitoring: Ensure high availability and low latency through auto‑scaling clusters, robust logging/metrics (Prometheus/Grafana), and drift‑detection across agent networks. Security & Compliance: Enforce secure communication, credential vaulting (HashiCorp Vault), and data encryption in flight and at rest for all agent interactions. Collaboration & Leadership: Partner with data scientists, software engineers, and product teams to translate business requirements into modular agent solutions; mentor junior developers in agent best practices. Must‑Have Skills & Experience Agent Frameworks: 3+ years hands‑on with LangChain and LangGraph (or equivalent graph‑based orchestration libraries). Multi‑Agent Systems: Proven track record designing and deploying collaborative agent crews, including master–worker and peer‑to‑peer topologies. LLM Expertise: Deep experience fine‑tuning and integrating large language models (OpenAI, Anthropic, or open‑source) for retrieval‑augmented and planning use cases. CI/CD & MLOps: Strong DevOps background on one or more hyperscalers (AWS, Azure, GCP) for automated build, test, and deploy of agent services. Containerization & Orchestration: Expert in Docker, Kubernetes, Helm; comfortable defining StatefulSets, Jobs, and custom operators for agent workloads. Event‑Driven Architectures: Solid understanding of message buses (Kafka, RabbitMQ) or serverless event triggers for inter‑agent communication. Security Best Practices: Experience implementing RBAC, secrets management, and network policies in production environments. Collaboration: Exceptional written and verbal communication, capable of leading cross‑functional design reviews and knowledge‑sharing sessions.

Keyword: Python

Price: $60.0

Python ML Automation Artificial Intelligence Artificial Neural Network Machine Learning LangChain Hugging Face