Role Description

• As a Senior Value Engineer specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• 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) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Who We Are

Atlas Energy Solutions Inc. (NYSE: AESI) is a leading solutions provider to the energy industry. Atlas’ portfolio of offerings includes oilfield logistics, distributed power systems, and the largest proppant supply network in the Permian Basin. With a focus on leveraging technology, automation, and remote operations to enhance efficiencies, Atlas is centered around a core mission of improving human beings’ access to hydrocarbons that power our lives and, by doing so, maximizing value creation for our shareholders.

Sr. Reliability Engineer

The primary role of the Sr. Reliability Engineer is to identify and manage asset reliability risks that could adversely affect plant or business operations. This position will be responsible for tracking plant downtime and driving root cause corrective action for all equipment failures to achieve world class equipment reliability. This role will work closely with site leadership to prioritize and execute improvement projects related to equipment reliability. This requires excellent attention to detail, high communication across departments and excellent analytical skills.

Responsibilities: 

• Responsible for daily oversight of equipment performance
• Addressing and predicting equipment failures
• Ensure correct KPIs are in place for monitoring equipment condition
• Analyze equipment trends to predict failures and recommend remediation
• Develop and execute projects to automate and/or simplify data collection and evaluation
• Establish statistical process controls for trend analysis and automatic notifications
• Design and execute experiments to qualify component improvements and new part vendors
• Responsible for investigating and reporting on all equipment failures and develop RCCA
• Oversee improvement projects using sound statistical method, DMAIC
• Downtime tracking and comparison tracking
• Strong mechanical knowledge of equipment
• Establish and develop strong relationship with Maintenance
• Any other duties as assigned

Qualifications:

• Bachelor's degree in Engineering – Mechanical, Materials or related
• Minimum 5 years related experience
• Recent experience in Manufacturing, Chemical Processing, Bulk Material Handling or Mining Environment
• Advanced Excel skills
• Strong statistical background, experience with SPC and Six Sigma
• Proven track record of process improvement
• Ability to multitask and work in a fast-paced environment
• Strong work ethic with a defined sense of urgency
• Great communication skills
• Organized self-starter that works well in a team environment
• Strong attention to detail and retention of pertinent information

 What You’ll Love About Us:

• Best People and Great Places to Work, Hire Vets ,Top Place to Work For – Austin American Statesman
• Your Well-Being is a 100% covered Medical, Dental, and Vision
• Invest in Your 401K with company match, immediate vesting