Senior Computer Scientist - Agentic AI
Adobe · Posted Oct 5
Creative software, document productivity, and digital marketing solutions
NoidaFull-timeOnsiteLead/Staff10+ years₹55.0L–₹90.0L yearly100+ applicants
SoftwareDigital MediaCreative SoftwareDocument ProductivityCustomer Experience ManagementMarketing TechnologyPublic Company
Full time
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About the role
Adobe builds large-scale enterprise software platforms that power customer experiences worldwide, where performance, reliability, security, scalability, and engineering excellence are fundamental requirements. The team works on Generative AI and agentic technologies applied to enterprise software, combining LLMs with enterprise data, tools, APIs, and workflows. This role will shape architecture and build scalable distributed systems, production-grade GenAI and agentic systems, agent orchestration and evaluation frameworks, while influencing technical direction across teams.
What you will 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.
- 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.
Skills used in this role
JavaPythonREST APIsMicroservicesDistributed SystemsObject-Oriented DesignData StructuresAlgorithmsConcurrencyGenerative AILLMsRAGEmbeddingsContext ManagementTool CallingModel SelectionLLM EvaluationAgentic AIMulti-Agent SystemsHuman-in-the-LoopCloud PlatformsEvent-Driven ArchitectureDatabasesCachingMessaging Systems
What the employer is looking for
- 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.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Adobe
Adobe Inc. is a global software company widely known for its creative, publishing, and document productivity tools, including Photoshop, Illustrator, Premiere Pro, and Acrobat. The company operates major cloud platforms—Creative Cloud, Document Cloud, and Experience Cloud—serving individual creators, small businesses, and large enterprises worldwide. Adobe has increasingly integrated powerful generative AI capabilities like Adobe Firefly and Acrobat AI Assistant into its product ecosystem.
- Industry
- Software
- Company size
- 31360+ employees
- Founded
- 1982-12-01
- Location
- San Jose, California, USA
- Funding stage
- Public Company
Funding
Public Company
Apple
- 1985-01-01Series A
Leadership
SN
Shantanu Narayen
Chair and Chief Executive Officer
SD
Steven Day
Interim Chief Financial Officer
DW
David Wadhwani
President, Creativity and Productivity Business
AC
Anil Chakravarthy
President, Customer Experience Orchestration Business
GC
Gloria Chen
Chief People Officer and Executive Vice President, Employee Experience
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