Level

Adobe

Senior Computer Scientist - Agentic AI

AI in this role

ragai-agentsai-evaluation

The Opportunity

Adobe builds products that power millions of customer experiences worldwide. Behind these experiences are sophisticated large-scale business software platforms, where performance, reliability, security, scalability, and engineering excellence are fundamental requirements.

We seek a Senior Computer Scientist with strong Java/Python skills and extensive experience in enterprise software development. This person is passionate about using Generative AI and agentic technologies to tackle complex client and organizational challenges.

In this role, you will combine strong enterprise engineering fundamentals with generative AI and autonomous AI. You will build intelligent systems that understand context, analyze enterprise knowledge, use tools and services, orchestrate complex workflows, and drive tasks toward meaningful outcomes.

You will shape architecture, build scalable distributed systems, make critical technical decisions, and influence solutions that span multiple components, services, and teams.

We value engineers who are hard-working, proactive, and passionate about delivering results. They challenge assumptions, fix problems at the root, make pragmatic tradeoffs, and take responsibility for making their systems better, more reliable, and easier to develop.

What You'll Do

  • Own and evolve significant technical areas end-to-end — from understanding ambiguous problems and defining the right solution through architecture, implementation, production validation, and long-term evolution.
  • Develop and implement scalable enterprise systems using Java and Python, with strong focus on architecture, APIs, distributed processing, concurrency, scalability, reliability, and maintainability.
  • Design and build production-grade GenAI and agentic systems that combine LLMs, enterprise data, tools, APIs, workflows, and context to solve complex business problems.
  • Build agentic workflows and architectures including planning, reasoning, tool use, workflow orchestration, context management, RAG, memory, human-in-the-loop experiences, and agent-to-agent collaboration.
  • Integrate AI agents with enterprise platforms and services, enabling agents to securely discover, retrieve, reason over, and act upon enterprise data and capabilities through APIs and tools.
  • Build reliable AI orchestration and execution frameworks that enable agents to interact with enterprise services while maintaining security, access control, observability, reliability, and predictable execution.
  • Build for non-deterministic AI systems by establishing mechanisms for evaluation, quality measurement, experimentation, telemetry, and continuous improvement.
  • Own outcomes, not just tasks — proactively identify gaps, risks, and opportunities and drive them to closure with minimal direction.
  • Solve complex problems across boundaries, collaborating with engineers, architects, product managers, data scientists, and other teams to deliver cohesive enterprise solutions.
  • Build for operational excellence with strong focus on speed, dependability, safety, observability, maintainability, scalability, and efficient resource utilization.

What You Need to Succeed

  • B.Tech/M.Tech in Computer Science or a related field, or equivalent practical experience.
  • 10+ years of hands-on software engineering experience, with a strong track record of designing, building, and operating complex business-critical software platforms.
  • Strong expertise in Java and/or Python, with experience building production-grade backend services, APIs, distributed applications, and enterprise platforms.
  • Strong foundation in data structures, algorithms, object-oriented design, distributed systems, and computer science fundamentals.
  • Strong understanding of enterprise architecture, microservices, APIs, distributed systems, concurrency, scalability, and performance engineering.
  • Experience crafting and building large-scale corporate software solutions with strong understanding of multi-tenancy, scalability, reliability, backward compatibility, security, observability, and workload management.
  • Experience with cloud platforms and distributed infrastructure, including designing, deploying, and operating production services at scale.
  • Deep knowledge of Generative AI and LLM-based application architectures, including prompting, RAG, embeddings, context management, tool calling, model selection, and LLM evaluation.
  • Hands-on experience or strong technical understanding of agentic AI architectures, including agents, orchestration, planning, tool use, workflow execution, memory/context management, multi-agent systems, and human-in-the-loop patterns.
  • Experience integrating LLM-powered systems with enterprise applications, APIs, data platforms, and business workflows.
  • Understanding of the challenges involved in building probabilistic AI systems, including hallucination mitigation, grounding, evaluation, latency, cost, observability, security, and reliability.
  • Experience with AI evaluation and telemetry, including defining metrics and feedback loops to continuously measure and improve GenAI and agentic system quality.
  • Strong experience with REST APIs, asynchronous processing, event-driven architectures, databases, caching, messaging systems, and cloud-native technologies.

What Success Looks Like

Success in this role is not measured only by the features you deliver. You will be successful when you:

  • Manage and enhance significant enterprise technical areas with minimal direction and strong technical judgment.
  • Turn ambiguous, complex problems into clear technical direction and executable solutions.
  • Build scalable, reliable, secure, and production-ready agentic AI systems that solve meaningful customer and business problems.
  • Design agentic architectures that effectively combine LLMs, enterprise knowledge, tools, APIs, workflows, and specialized agents.
  • Enable AI agents to reason over enterprise context and take meaningful actions across enterprise systems, while maintaining appropriate security, governance, and control.
  • Establish strong engineering foundations for AI quality, evaluation, observability, reliability, security, and continuous improvement.
  • Make architecture decisions that balance scalability, reliability, maintainability, AI quality, latency, cost, security, and long-term evolution.
  • Influence technical direction across teams and organizational boundaries through technical depth and credibility.
  • Raise the technical bar through mentorship, architecture leadership, GenAI expertise, and engineering practices that benefit the broader organization.

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

Senior Computer Scientist - Agentic AI at Adobe rates 90 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.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

RAGAI AgentsAI Evaluation

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. How do you decide that one model's output is better than another's for a given task?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: RAG, AI Agents, and AI Evaluation. 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.

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.

Get a free CV review

Get new AI jobs (Builds AI ●●●●) by email

One email a week with the new AI jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.

Similar roles

Other roles that build AI, at other companies.

What kind of AI work fits you?

Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.

Find my next step

More jobs at Adobe

Related searches

Same AI level