Senior AI Agent Engineer, Brand Concierge
Role details
Job location
Tech stack
Job 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 (e.g., 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
Requirements
- 3-5+ years of experience in AI/ML engineering, NLP systems, or backend development
- Strong proficiency with LLM frameworks (e.g., 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
Benefits & conditions
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $172,500 -- $306,625 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
In California, the pay range for this position is $211,800 - $306,625
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
