Software Development Engineer, Full Stack (ai/agents) – Developer Platforms

Adobe Adobe · Enterprise · Bangalore, India +1

Full Stack Software Engineer to build AI-powered agentic experiences for Adobe's internal developer platform, focusing on LLM orchestration, tool use, and multi-agent workflows.

What you'd actually do

  1. Design, develop, and test full-stack features end-to-end for the internal developer portal and enterprise knowledge hub, spanning React frontends, Node.js and Python backend services, and AI orchestration layers.
  2. Build LLM-powered capabilities including agent planning, tool/function calling, memory management, and multi-agent workflow orchestration to help engineers find knowledge and get work done.
  3. Develop and integrate APIs that allow agents to discover and act across Adobe's internal services and knowledge sources, with a focus on reliability and correctness.
  4. Design orchestration patterns that coordinate multiple agents, tools, and data sources to accomplish complex engineering tasks and answer knowledge queries.
  5. Investigate and resolve production issues across the stack, contributing to operational excellence, evaluation, and monitoring of AI systems.

Skills

Required

  • Bachelor's degree or equivalent experience in Computer Science, Software Engineering, or a related field with 4- 6 years of professional software development experience.
  • Strong full-stack proficiency with JavaScript/TypeScript, React, and Node.js.
  • Solid backend engineering experience with Python and designing/consuming REST APIs.
  • Hands-on experience building with LLMs, including prompt design, function/tool calling, and integrating model APIs into applications.
  • Experience with agentic concepts such as LLM-based planning, memory management (short- and long-term context), and multi-agent workflow design.
  • Familiarity with API orchestration — coordinating multiple services, tools, and data sources into coherent workflows.
  • Working knowledge of cloud platforms (AWS, Azure, or GCP) and modern deployment practices.
  • Strong problem-solving ability, good communication skills, and comfort operating across the full stack in a fast-moving environment.

Nice to have

  • Experience with agent frameworks and protocols (e.g., LangChain, LangGraph, Model Context Protocol / MCP, A2A, or similar).
  • Familiarity with RAG, vector databases, embeddings, and semantic search — especially applied to knowledge bases and documentation.
  • Experience evaluating and testing non-deterministic AI systems (evals, guardrails, observability).
  • Experience building internal developer portals, knowledge bases, or developer productivity tooling.
  • Exposure to Adobe's React Spectrum design system or similar component libraries.
  • Experience with serverless runtimes, microservices, or event-driven architectures.

What the JD emphasized

  • agent planning
  • tool/function calling
  • memory management
  • multi-agent workflow orchestration
  • API orchestration
  • evaluating and testing non-deterministic AI systems

Other signals

  • building agentic workflows
  • LLM-powered tools
  • internal developer experience