Software Engineer II

UiPath UiPath · Enterprise · Bangalore, India · Engineering

Software Engineer II role at UiPath focused on building and scaling an AI agentic orchestration platform. The role involves full-stack development, hands-on coding with AI tools, prototyping, measuring system quality, and ensuring reliability of distributed systems. Requires experience with production AI systems, LLMs, multi-agent architectures, orchestration frameworks, and distributed systems.

What you'd actually do

  1. Design, develop, and maintain full stack for Vertical Solutions products leveraging AI Coding Assistants.
  2. Write production-quality code daily, leveraging AI tools (Claude, GitHub Copilot, etc.) to enhance your development workflow
  3. Take ideas from Prototype to validate with real customers and turn the ones that prove value into production systems.
  4. Design evaluations, measure quality against real customer data, and understand when metrics mislead. Our systems are often non-deterministic. Responsible shipping means measuring honestly, not chasing vanity numbers.
  5. Deeply understand who will use the features you build and why they need them, translating customer needs into elegant technical solutions

Skills

Required

  • production AI systems
  • LLMs
  • tool-calling
  • multi-agent architectures
  • orchestration frameworks (LangGraph, LangChain, or equivalent)
  • structured outputs
  • orchestration
  • evaluation of model behavior in real-world workflows
  • distributed systems experience
  • resilient systems with idempotency, replay ability, state management, and long-running jobs
  • analytical thinking
  • rapid prototyping
  • React
  • Python
  • C#
  • TypeScript
  • multithreading
  • asynchronous programming
  • synchronization
  • cloud-native programming models
  • Azure, AWS, or GCP
  • Docker
  • Kubernetes
  • AI coding tools and coding agents (e.g., GitHub Copilot, Cursor, Claude Code, or similar)
  • agile development
  • CI/CD
  • DevOps
  • infrastructure as code

Nice to have

  • healthcare Tech/ Finance Tech/ Procurement Tech systems experience
  • Data science and evaluation
  • applied ML techniques such as classification, anomaly detection, ranking, or predictive modeling
  • evaluating AI systems using experimentation, metrics, and empirical analysis to improve quality and reliability
  • Data and retrieval systems
  • large-scale data platforms (Snowflake, columnar warehouses, denormalized data models)
  • retrieval-heavy architectures, RAG systems, or citation-grounded AI workflows
  • Engineering for trustworthy AI
  • blending deterministic and probabilistic systems (rules engines + AI)
  • designing eval-driven systems, regression testing for LLM outputs, or human-in-the-loop review workflows
  • Platform and product development
  • Frontend familiarity

What the JD emphasized

  • AI agentic orchestration platform
  • Act 2 strategy
  • core orchestration engine
  • production AI systems
  • multi-agent architectures
  • orchestration frameworks
  • evaluation of model behavior
  • distributed systems
  • customer needs
  • highly scalable, reliable distributed systems

Other signals

  • AI agentic orchestration platform
  • Act 2 strategy
  • core orchestration engine
  • production AI systems
  • multi-agent architectures
  • orchestration frameworks
  • evaluation of model behavior