# Senior Applied Value Engineer - EAM - NAM

**Company:** [Celonis](https://hotfix.jobs/companies/celonis)
**Location:** Bengaluru, India
**Role:** Sales Engineering
**Experience:** 5+ years
**Skills:** Python, RAG, Prompt Engineering, LangChain, Llamaindex, pandas, Pydantic, scikit-learn, PyTorch, Llm Orchestration, Multi-Agent Systems, Function Calling, Aws Bedrock, Azure Ai, Google Cloud Vertex
**Posted:** 2026-07-24

> Leads technical pre-sales and end-to-end Proof-of-Value delivery for strategic customers, translating AI strategies and business challenges into scalable Celonis solutions. Requires 5+ years of technical pre-sales experience, Energy or Oil & Gas expertise, generative AI knowledge, Python, and strong executive presentation skills.

## Job Description

## Responsibilities

- Understand customers’ AI strategies and business-critical challenges, identify problem-solution fit, and translate requirements into innovative Celonis solutions.
- Build creative prototypes using AI technologies during customer hackathons.
- Enable agentic process transformation by helping customers achieve ROI from AI deployments at scale.
- Execute business-critical Proof-of-Value projects end to end, including architecture and delivery of secure, scalable LLM and agent systems with RAG, tools, and guardrails.
- Integrate solutions with enterprise data, identity, and compliance frameworks.
- Remain involved through project completion until agreed value and adoption thresholds are reached.
- Develop domain or industry specialization, including Energy and Oil & Gas.
- Present solutions to internal and external stakeholders, including executives, through whiteboarding sessions, formal readouts, and demonstrations.

## Requirements

- 5+ years of experience leading technical pre-sales, including defining AI roadmaps, building ROI/TCO business cases, and prototyping machine learning and generative AI solutions.
- Experience in the Energy, Oil & Gas industry.
- Understanding of generative AI techniques such as RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, and fine-tuning.
- Understanding of business processes across sectors such as Supply Chain and Finance, with the ability to translate business needs into AI use cases.
- Good knowledge of Python and common machine-learning libraries and data-engineering technologies.
- Strong presentation skills for internal and external stakeholders, including executives.
- Bachelor’s degree required.
- Master’s degree in computer science, engineering, mathematics, or a related field, or equivalent work experience preferred.

## Nice to Haves

- Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, with safety evaluations and guardrails.
- Working knowledge of LLM ecosystem tools such as LangChain, LlamaIndex, or other open-source packages.
- Experience deploying and monitoring models at scale on AWS Bedrock, Azure AI, or Google Cloud Vertex.

## Compensation and Benefits

- Restricted Stock Units and merit-based refresh grants for full-time employees.
- Inclusive parental leave: 24 weeks fully paid for primary carers and 12 weeks for supporting carers.
- Unlimited PTO in applicable regions and generous PTO globally.
- Flexible hybrid work model.
- Learning framework, mentorship programs, and access to a dedicated learning platform.
- Subsidized Wellhub memberships, mental health counseling, and Wellness Weeks.
- Paid time off for annual community and environmental volunteering.

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