Senior Applied Value Engineer - Uki Oil & Gas

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

Senior Applied Value Engineer at Celonis, focusing on building and prototyping AI solutions for enterprise customers using the Celonis Process Intelligence Platform and leading AI technologies (e.g., OpenAI, Microsoft). The role involves understanding customer challenges, demonstrating value, and implementing agentic AI systems with RAG, tools, and guardrails to drive ROI and scale AI deployments.

What you'd actually do

  1. AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
  2. Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
  3. Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
  4. Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
  5. Ensure Successful Project Outcome: Senior Applied Value Engineer stay involved with projects until agreed value & adoption thresholds are reached

Skills

Required

  • 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
  • Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
  • Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
  • Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
  • Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
  • Bachelor’s Degree required

Nice to have

  • Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
  • Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
  • Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).
  • Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

What the JD emphasized

  • building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners
  • industrialize AI unlocking real ROI on AI deployments and at scale
  • Agentic Process Transformation
  • autonomous AI agents
  • LLM/agent systems with RAG, tools, and guardrails

Other signals

  • customer-facing
  • prototyping
  • AI solutions
  • LLM/agent systems
  • ROI