> Markdown version of [/jobs/ext/2624628-senior-ai-agent-engineer-brand-concierge](https://www.wearedevelopers.com/jobs/ext/2624628-senior-ai-agent-engineer-brand-concierge). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Agent Engineer, Brand Concierge - **Company:** Adobe Inc. - **Location:** San Jose, CA, United States - **Experience:** Expert - **Salary:** $162,000.0 - $301,200.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Communications Protocols, DevOps, Python (Programming Language), Machine Learning, Management of Software Versions, Grafana, Multi-Agent Systems, Prompt Engineering, Backend, Containerization, Kubernetes, Information Technology, Virtual Agents, Restful APIs, GPT, Docker, Data Generation - **Published:** August 31, 2026 - **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-A5938640515D63629A/ ## About the Role * 3-5+ years of experience in AI/ML engineering, NLP systems, or Back End development * Strong proficiency with LLM frameworks (eg, OpenAI APIs, LangChain, RAG pipelines) * Experience building conversational agents or workflow bots in production environments * Familiarity with cloud platforms (AWS/GCP/Azure), REST APIs, Python, and containerization (Docker, K8s) * Comfort with prompt design, vector databases, and memory handling strategies, * Experience with multi-agent frameworks or agent orchestration systems * Familiarity with observability tools, data labeling workflows, or synthetic data generation * Background in conversational design or dialogue management systems * Degree in Computer Science, Data Science, Engineering, or a related field ## Description We are looking for a hands-on, systems-oriented AI Agent Engineer to design, build, and maintain intelligent agents that drive automation and business impact across the enterprise. This role is responsible for the full lifecycle of agent development - from design to versioning, orchestration, and continuous learning. You'll contribute directly to scaling our AI strategy by engineering reusable components, optimizing agent workflows, and ensuring real-world performance in production environments. What You'll Do * Agent Development: Build and fine-tune specialized AI agents for targeted customer experience use cases such as discovery, support, and lead qualification * Implement prompt engineering strategies, memory handling, resource management and tool-calling integrations * Multi-Agent Communication: Adopt agent-to-agent communication protocols and handoff mechanisms to enable cooperative task execution and delegation * Build orchestrated workflows across agents using frameworks like LangChain, AutoGen, or Semantic Kernel * Templates & Reusability: Create reusable agent templates and modular components to accelerate deployment across business units * Build plug-and-play configurations for domain-specific requirements * Lifecycle Management & Monitoring: Track and improve conversation quality, task success rate, user satisfaction, and performance metrics * Automate monitoring of agent behavior using observability tools (eg, Arize, LangSmith, custom dashboards) * Continuous Improvement: Implement learning workflows, including human-in-the-loop feedback and automatic retraining * Refine prompts and model behavior through structured experimentation and feedback loops * Maintenance & Governance: Handle knowledge base updates, drift detection, performance degradation, and integration of new business logic * Ensure agents stay aligned with evolving enterprise data sources and compliance requirements * Deployment: Manage agent versioning, testing pipelines (unit, regression, UX), and controlled rollout processes * Collaborate with DevOps, QA, and infrastructure teams to ensure scalable deployments ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [AI Agents & Agentic AI](https://www.wearedevelopers.com/videos/2017-ai-agents-agentic-ai) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Prompt Engineering is a Job of the Past](https://www.wearedevelopers.com/magazine/342-prompt-engineering-is-a-job-of-the-past)