Software Development Engineer 3

AI in this role

Design and develop backend services integrating LLMs, RAG, and AI agents into Adobe's enterprise integration platform.

openaiclaudegeminicopilotpineconepgvectormilvuscursorjavaspringkafkamongodb+2

prompt-engineeringragllm-integrationai-agentsai-safetybackend-engineeringai-integrationdistributed-systems

About the iPaaS Team

Our iPaaS team builds and operates Adobe’s enterprise integration platform, enabling reliable, scalable connectivity across business-critical applications and data platforms. The platform spans API and event-driven integrations, Kafka-based streaming, cloud services, data synchronization, and self-service integration capabilities.

We are now evolving the platform with AI-powered engineering and agentic automation—building intelligent agents that can monitor integrations, perform automated triage and root-cause analysis, recommend or execute remediation, and simplify integration development and operations.

If you are passionate about distributed systems, event-driven architecture, Kafka, Java, cloud platforms, and AI agents, this is an opportunity to build foundational capabilities used across Adobe at scale.

Role Overview

We are looking for a Senior Backend Java Engineer – Kafka & Agentic AI to design and develop high-volume, highly available backend services powering Adobe’s enterprise integration platform.

In this role, you will work across Java/Spring, Kafka and event-driven architectures, while integrating LLMs, RAG, MCP and AI agents into platform services. You will build intelligent capabilities for automated monitoring, triage, RCA, remediation and developer self-service.

Required Skills & Expertise

Java Core & Frameworks: 5–7 years of experience building scalable, multithreaded server-side applications using Java/Java EE, Spring Framework, and object-oriented design patterns.
Data & Performance: Deep proficiency with Relational Databases (SQL, high-performance transactional queries) and MongoDB, using ORMs (JPA2, Hibernate) optimized for speed and scalability.
AI/ML Integration: Hands-on experience integrating LLMs/AI APIs (OpenAI, Claude, Gemini) into Java services using frameworks like Spring AI or LangChain4j, including prompt engineering and context management.
AI Infrastructure & RAG: Familiarity with vector databases (e.g., Pinecone, Milvus, pgvector) and Retrieval-Augmented Generation (RAG) architecture to build reliable backend features.
Modern AI Practices: Practical experience with AI-assisted dev tools (Copilot, Cursor) alongside an understanding of model deployment, cost/latency optimization, and responsible AI guardrails (privacy, hallucination mitigation).

About Adobe

Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.

Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.

Let’s Adobe together

At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.

Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com.

AI Use Guidelines for Interviews:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience.

How we rate this

Software Development Engineer 3 at Adobe rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAGLLM IntegrationAI AgentsAI SafetyBackend EngineeringAI IntegrationDistributed Systems

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How have you integrated a large language model into a production application?
How do you decide when an AI agent can act on its own versus asking for approval first?
How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

List these exact terms on your resume: Prompt Engineering, RAG, LLM Integration, AI Agents, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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