Conversation AI Engineer

We are looking for a Conversation AI Specialist who builds agentic, process-aligned dialogue systems — not scripted chatbots. You will build the conversational intelligence layer of our advisor efficiency platform. It includes timely orchestration, intent reasoning, and LLM-powered assist systems that help advisors during complex customer interactions across chat, phone, and ecommerce. You will own the full conversation stack, from utterance to action.
Key Responsibilities
Agentic Conversation Design:
Architect and build the conversational layer of our prompt-based agentic platform — including intent detection, dialogue orchestration, and multi-step reasoning flows aligned to advisor workflows.
LLM Integration & Prompt Engineering:
Design and maintain the prompt architecture that drives advisor-assist features — including context injection, tool-calling patterns, guardrails, and output validation.
Advisor Assist Systems:
Build real-time AI tools that surface relevant knowledge, suggest responses, and guide advisors through commerce, subscription, and support interactions.
Process Mapping:
Work with operations and product teams to deeply understand advisor business processes, then translate that understanding into conversation system design.
Evaluation & Quality:
Define conversation quality metrics, build evaluation datasets from real interaction logs, and operate a continuous improvement loop for deployed systems.
Probabilistic Fallback Design:
Design graceful degradation patterns — ensuring the system handles low-confidence states, ambiguous intents, and out-of-scope inputs without advisor disruption.
Cross-platform Delivery:
Integrate conversational AI features throughout chat, phone, and ecommerce advisor surfaces — maintaining coherent behavior across channels.
Attitude & Approach We're Hiring For
Beyond technical skills, we are specifically hiring for three attitude shifts that define success in this role:
Process-aligned composition:
you build conversation flows that mirror advisor operational workflows — not abstract dialogue trees disconnected from how work actually happens.
Probabilistic reasoning:
you architect systems where intent is inferred, confidence is tracked, and ambiguity is handled gracefully rather than failing hard.
Data-driven iteration:
you measure conversation quality with data, not intuition — defining metrics, curating evaluation sets, and iterating based on evidence.
Required Qualifications
3–5 years in conversational AI, NLP engineering, or LLM-based product development.
Experience building dialogue systems with real business process alignment, not just scripted flows.
Proficiency in Python and NLP tooling
Strong understanding of intent classification, entity extraction, and context management in stateful conversations.
Experience deploying conversational AI to production with real user traffic.
Ability to build for uncertainty — confidence scoring, fallback handling, human-in-the-loop blocking issue.
Preferred Qualifications
Experience building agentic systems with tool use, function calling, or multi-step LLM orchestration. Familiarity with RAG for knowledge-grounded responses.
About Adobe
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