Senior Computer Scientist - Agentic AI

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,