Agent Architect Agentic Systems
Agent Architect Agentic Systems
xenonstack momentsThis job is no longer accepting applications
Job Description
About Xenonstack
XenonStack is the fastest-growing Data and AI Foundry for Agentic Systems, enabling people and organizations to gain real-time and intelligent business insights.
We Deliver Innovation Through
THE OPPORTUNITY
We are seeking an Agent Architect to design and lead the architecture of multi-agent systems, enabling enterprises to adopt Agentic AI at scale.
This role goes beyond traditional software or ML architecture — you will define how LLMs, tools, memory, and orchestration frameworks come together to form reliable, adaptive, and compliant AI agents.
If you are passionate about system design, orchestration, and Responsible AI, this role is your opportunity to shape the foundation of the AgentOps ecosystem.
Key Responsibilities
Must-Have
XENONSTACK CULTURE – JOIN US & MAKE AN IMPACT!
At XenonStack, we believe in shaping the future of intelligent systems. We foster a culture of cultivation built on bold, human-centric leadership principles, where deep work, simplicity, and adoption define everything we do.
Our Cultural Values
XenonStack is the fastest-growing Data and AI Foundry for Agentic Systems, enabling people and organizations to gain real-time and intelligent business insights.
We Deliver Innovation Through
- Agentic Systems for AI Agents akira.ai
- Vision AI Platform xenonstack.ai
- Inference AI Infrastructure for Agentic Systems nexastack.ai
THE OPPORTUNITY
We are seeking an Agent Architect to design and lead the architecture of multi-agent systems, enabling enterprises to adopt Agentic AI at scale.
This role goes beyond traditional software or ML architecture — you will define how LLMs, tools, memory, and orchestration frameworks come together to form reliable, adaptive, and compliant AI agents.
If you are passionate about system design, orchestration, and Responsible AI, this role is your opportunity to shape the foundation of the AgentOps ecosystem.
Key Responsibilities
- Architecture Design
- Define blueprints for agent workflows, including reasoning loops, tool integration, memory systems, and multi-agent orchestration.
- Architect scalable, modular, and extensible agentic systems aligned with enterprise needs.
- Context & Memory Orchestration
- Design context pipelines using RAG, knowledge graphs, APIs, and multi-tiered memory (short-term, episodic, long-term).
- Ensure efficient token management and context allocation for reliability and cost efficiency.
- Integration & Ecosystem
- Build frameworks to connect LLMs, APIs, enterprise data sources, and observability layers.
- Collaborate with AgentOps Engineers to ensure smooth deployment and monitoring.
- Reliability & Governance
- Implement guardrails for safety, compliance, and brand alignment.
- Ensure architectures meet Responsible AI and governance standards.
- Innovation & Strategy
- Stay ahead of emerging frameworks (LangGraph, MCP, AgentBridge, A2A messaging) and incorporate them into architecture strategy.
- Partner with product managers and executives to align agent design with enterprise workflows and outcomes.
- Leadership & Mentorship
- Guide AI engineers, AgentOps specialists, and product teams in best practices for agent design.
- Mentor teams on evaluating trade-offs between accuracy, cost, latency, and compliance.
Must-Have
- 6–10 years in AI/ML engineering, systems architecture, or enterprise software design.
- Deep knowledge of LLM architectures, orchestration frameworks (LangChain, LangGraph, LlamaIndex), and agent design patterns.
- Strong understanding of context engineering, RAG pipelines, and vector/knowledge databases.
- Experience with multi-agent orchestration frameworks (MCP, A2A messaging, AgentBridge).
- Proficiency in Python and AI development stacks.
- Familiarity with cloud-native architecture (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).
- Solid understanding of Responsible AI frameworks and compliance-driven system design.
- Background in Reinforcement Learning (RLHF, RLAIF, reward modeling).
- Experience in enterprise-scale deployments in BFSI, GRC, SOC, or FinOps.
- Prior experience as a Solutions Architect, AI Architect, or Technical Lead.
- Contributions to open-source frameworks in multi-agent systems or LLM orchestration.
- Agentic AI Product Company
- A Fast-Growing Category Leader
- Career Mobility & Growth
- Global Exposure
- Create Real Impact
- Culture of Excellence
- Responsible AI First
XENONSTACK CULTURE – JOIN US & MAKE AN IMPACT!
At XenonStack, we believe in shaping the future of intelligent systems. We foster a culture of cultivation built on bold, human-centric leadership principles, where deep work, simplicity, and adoption define everything we do.
Our Cultural Values
- Agency – Be self-directed and proactive.
- Taste – Sweat the details and build with precision.
- Ownership – Take responsibility for outcomes.
- Mastery – Commit to continuous learning and growth.
- Impatience – Move fast and embrace progress.
- Customer Obsession – Always put the customer first.
- Obsessed with Adoption – Making AI agents enterprise-ready and accessible.
- Obsessed with Simplicity – Turning complex orchestration into seamless, intuitive workflows.
More Info
Key Skills
agent design patterns
LangChain
orchestration frameworks
vector knowledge databases
AgentBridge
AI development stacks
cloud-native architecture
multi-agent orchestration frameworks
context engineering
Responsible AI frameworks
LangGraph
A2A messaging
LLM architectures
RAG pipelines
container orchestration
LlamaIndex
