Applied AI Engineer

Celonis Celonis · Data AI · Bangalore, India · Value Engineering

Applied AI Engineer role at Celonis, focusing on building production-ready predictive, generative, and agentic AI solutions for the Finance and Accounting domain. The role involves end-to-end development, including designing and building LLM-based copilots and autonomous agents with guardrails and audit trails, and embedding AI features into the product. Requires significant experience in AI/ML, LLMs, and agentic systems, with a focus on production deployment and MLOps.

What you'd actually do

  1. Design and build predictive models, generative AI features, and multi-agent systems tailored to business problems.
  2. Develop LLM-based copilots and autonomous agents, including human-in-loop flows, security guardrails, and audit trails.
  3. Work closely with software engineers and data scientists to embed AI features into the product.
  4. Build and maintain secure, scalable MLOps pipelines for training, deployment, and monitoring.
  5. Continuously evaluate and improve model performance and user impact.

Skills

Required

  • Python
  • TensorFlow
  • PyTorch
  • scikit-learn
  • AWS/Azure/GCP
  • GitHub/GitLab
  • multi-agent architectures
  • memory systems
  • tool-use
  • orchestration
  • routing
  • safety guardrails
  • autonomous or semi-autonomous agents
  • governance
  • logging
  • human-in-loop flows
  • predictive modeling
  • NLP
  • ML algorithms
  • statistics
  • model deployment
  • data pipelines
  • version control
  • CI/CD practices
  • web fundamentals (HTTP, JSON, authentication)
  • REST APIs

Nice to have

  • R
  • Java

What the JD emphasized

  • production-ready AI and agentic systems
  • production-grade AI and agentic systems
  • 1+ year of experience building agentic systems (production-ready, not POCs)

Other signals

  • build production-ready AI and agentic systems
  • end-to-end development
  • LLM-based copilots and autonomous agents
  • MLOps pipelines