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About This Role
AI Agent Systems ArchitectAzumo, a leading AI Development company, is seeking a highly motivated AI Agent Systems Architect to join our growing team of expert AI developers. We specialize in delivering Top AI Development services, helping organizations build intelligent applications powered by Generative AI, large language models (LLMs), and advanced automation. As part of our team, you will collaborate with engineers, data scientists, and domain experts across SaaS, cloud, and big data environments. You will work on cutting\-edge agentic architectures, translating research into production\-ready solutions that drive real\-world impact for global clients. At Azumo, you’ll thrive if you enjoy the full lifecycle of Generative AI development—from ideation and prototyping to deployment, monitoring, and scaling intelligent applications.
Responsibilities in AI Development
Architect, design, and actively write code for production\-grade stateful multi\-agent systems, custom state machines, and function\-calling workflows using frameworks such as LangGraph, CrewAI, or native Python execution loops.
Lead full\-cycle hands\-on development: data preparation, tool integration via Model Context Protocol (MCP), structured output enforcement, context\-window recovery/caching, containerization, and secure cloud deployment (Azure/AWS).
Implement MLOps/LLMOps evaluation pipelines (e.g., Langfuse, Ragas) for automated prompt regression tracking, hallucination mitigation, and human\-in\-the\-loop (HITL) gating.
Apply Responsible AI practices and guardrails throughout solution delivery to ensure system reliability and safety.
Translate business and mission requirements into technical designs; prototype and iterate quickly with stakeholders using AI\-accelerated workflows.
Contribute to Azumo’s innovation roadmap by identifying research topics, publishing insights, and advancing our AI software development services portfolio.
About Azumo
Based in San Francisco, California, Azumo is an innovative software development firm specializing in AI software development services. We help companies of all sizes build intelligent applications by combining expertise in data, cloud, and AI. Our talented AI developers are trusted to deliver Top AI Development services in Generative AI, intelligent automation, and custom machine learning solutions. At Azumo, we believe in professional and personal growth. As a recognized AI Development company, we support our engineers in mastering the latest technologies and delivering Top AI Development services worldwide. Our culture emphasizes collaboration, continuous learning, and solving complex problems with modern AI solutions. We believe in giving back to our community and will volunteer our time to philanthropy, open\-source initiatives and sharing our knowledge. If you are qualified for the opportunity and looking for a challenge please apply online at Azumo/join\-our\-team or connect with us at [email protected]
Requirements Basic Qualifications:
- Bachelor’s Degree in Computer Science, Data Science, or related field (Master’s is a plus).
- 3\+ years of experience developing and deploying ML, NLP, or Generative AI systems in production environments.
- Expert\-level skills in Python and software engineering fundamentals (data structures, async programming, API design, testing, CI/CD, Git, containers).
- Hands\-on experience with stateful AI agent frameworks and tooling: LangGraph, LangChain, CrewAI, MCP, and vector databases (Pinecone, LanceDB, Azure AI Search).
- Active experience utilizing modern AI\-assisted coding tools (e.g., Claude Code, Cursor, GitHub Copilot) to accelerate development and codebase analysis.
- Proven cloud deployment experience (Azure preferred; AWS acceptable) using Docker and serverless/microservice architectures.
- Strong written and verbal communication skills to explain complex architectural concepts and trade\-offs to diverse audiences.
- Professional English proficiency (C1\).
Preferred Qualifications:
- Experience building Human\-in\-the\-Loop (HITL) workflows, automated evaluation suites, and deterministic fallback logic for LLMs.
- Contributions to research papers, open\-source AI libraries, or active participation in the AI engineering community.
Benefits
- Paid time off (PTO)
- U.S. Holidays
- Training
- Mentored career development
- Profit Sharing
- $US Remuneration
Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 4,317 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Azumo, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $240,000 based on 96 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Azumo AI Hiring
Azumo has 1 open AI role right now. They're hiring across AI Agent Developer. Based in US.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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