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Celonis, the global leader in Process Intelligence and Process Mining technology, is seeking an Applied AI Engineer to join the Sailfin Accounts Receivable (AR) Team in Bangalore. This product engineering team works in the Finance and Accounting domain, designing, developing, deploying, and maintaining large-scale AR solutions for global customers using a modern technology stack including AI/ML models, LLMs, multi-agent systems, cloud platforms, and automation frameworks.
In this role, you will build production-ready predictive, generative, and agentic AI solutions for the Finance domain. You will handle end-to-end development from identifying use cases to deploying AI features in production, working with real-world, production-grade AI and agentic systems rather than POCs.
Key responsibilities include partnering with product owners and finance experts to identify strong AI use cases in Accounts Receivable; designing and building predictive models, generative AI features, and multi-agent systems tailored to business problems; developing LLM-based copilots and autonomous agents with human-in-loop flows, security guardrails, and audit trails; collaborating with software engineers and data scientists to embed AI features into the product; building and maintaining secure, scalable MLOps pipelines for training, deployment, and monitoring; continuously evaluating and improving model performance and user impact; staying current with advancements in LLMs, NLP, and multi-agent frameworks; setting up AI demos for customers and stakeholders; and contributing to a culture of innovation and continuous learning.
Required experience includes 4+ years of AI/ML engineering, 3+ years with LLM-based solutions, and 1+ year building production-ready agentic systems. You should have strong understanding of multi-agent architectures, memory systems, tool-use, orchestration, routing, and safety guardrails. Technical skills required: strong Python programming (preferred), experience with TensorFlow, PyTorch, and scikit-learn, solid understanding of predictive modeling, NLP, ML algorithms, and statistics, cloud environment experience (AWS/Azure/GCP), GitHub/GitLab and CI/CD practices, and basic web fundamentals including HTTP, JSON, authentication, and REST APIs.
