About the Role

The New York Times is looking for a Software Engineer to help build our next generation of internal tools and services to support our production and publishing operations. We are rebuilding our manufacturing and publishing workflow systems in the latest cloud technologies, with a focus on microservices and serverless technology.

You'll work on systems that support our publishing workflow and plant manufacturing systems. You will work with the latest cloud-based technologies, building applications in serverless and container technology from back-end workflow engines, data mining, API, and websites. We are entirely cloud-focused; our group is completely invested in AWS Lambda functions and a variety of other serverless AWS Managed Services. You'll participate in discovery, analysis, requirements gathering, design, and implementation. You will help in transforming our systems and deployment methodologies to be aligned with the current best practices models.

You will be reporting to the Senior Director of the Publishing Technology Software Engineering team. Your teammates will be other Systems Analysts, Software Engineers, DevOps Engineers and Project Managers, all working in an Agile environment. You will work with internal customers company wide as you build applications that produce the world's greatest journalism.

This position is hybrid remote/in-office (2 days/3 days)

#LI-Hybrid

Responsibilities:

• As part of an internal application development team, you will develop internal applications in TypeScript, Node.j, and JavaScript.
• You will work on frontend and backend code bases.
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of software engineering experience
• Proficiency in TypeScript, Node.js, and JavaScript environments 
• Experience working with SQL and NoSQL databases 
• Familiarity with AI-assisted development tools such as GitHub Copilot 
• Experience building applications using React.js 
• Experience communicating with internal customers, technical peers, and management 
• Experience building applications on a major cloud provider (AWS or GCP) 
• Experience building and integrating APIs 
• Experience dissecting, understanding, and building complex systems

Preferred Qualifications:

• Experience with CI/CD tooling such as Terraform and Drone
• Experience building microservices and working with AWS Lambda, S3, API Gateway, SQS, DynamoDB, AWS RDS and other AWS serverless resources
• Some experience with C/C++ would be nice to have.

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-019167

Role Description

• As an Senior Value Engineer specializing in CPG and Fleet Logistics, you are pushing the envelope in solving business-critical problems for some of the world's most recognized consumer brands and global mobility networks. You will be working intimately with our most strategic enterprise clients, understanding their uniquely complex objectives—spanning from high-velocity beverage manufacturing and Direct Store Delivery (DSD) optimization to massive-scale fleet lifecycle management and dynamic asset routing. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers' massive supply chains, vehicle fleets, and distribution networks. This enables them to industrialize AI, unlocking real ROI on deployments at scale—ensuring products are always on the shelf and vehicles are always ready for the customer. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Chief Supply Chain Officers (CSCOs) and Fleet Operations Executives, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis across these premier global networks.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct supply chain challenges inherent to high-volume CPG and fleet mobility (e.g., predictive demand forecasting, route optimization, fleet predictive maintenance, dynamic asset allocation, and mitigating raw material volatility). As a Celonis product and logistics domain expert, translate these complex, physical-world challenges into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle within various manufacturing, distribution, and fleet management business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and telematics networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, and DSD execution.

• Agentic Process Transformation: Support these enterprise clients in achieving tangible ROI from AI at scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous fleet rebalancing, intelligent shipment exception handling, or automated trade promotion deductions).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs (e.g., SAP), Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and massive IoT/telematics data streams.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for CPG and Mobility Supply Chains, scaling knowledge across the organization regarding the nuances of fast-moving consumer goods and asset-heavy fleet operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, CPG/Beverage, or Fleet Logistics environments. This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume manufacturing and mobility (such as Direct Store Delivery (DSD), Order-to-Cash, Procure-to-Pay, Fleet Lifecycle Management, or Sales & Operations Planning) with the ability to translate high-level operational needs into specific 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., intelligent dispatch assistants, or automated extraction of data from complex vendor contracts and logistics documentation).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional and IoT datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, logistics directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, 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 suited for enterprise-grade supply chain environments.

• Familiarity with CPG and fleet-specific systems (e.g., SAP APO/IBP, Blue Yonder, Manhattan, or major telematics/fleet tracking platforms).

• 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).

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

Overview 

Flex is a growth-stage, NYC headquartered FinTech company that is creating the best rent payment experience. It’s hard to believe that it’s 2026 and paying rent on time is expensive, inflexible, and difficult. We’re here to change that! Flex enables our users to pay rent throughout the month on a schedule that better fits their finances and budget. Our mission is to empower as many renters as possible with flexibility over their most significant recurring expense. After deliberately keeping a stealth profile as we built up unprecedented investor support and an enthusiastic user base, we are looking for motivated individuals to help us keep our mission growing. Will you be a part of the team?

About the Role

Flex is looking for a Staff Software Engineer to join our core platform team. We want engineers with ideas (because they’ll definitely be heard on our small and tight-knit team) and ambition! Successful devs will feel comfortable in a startup environment and will be happy to work in a remote-first team with a lot of independence. As a Staff Engineer at Flex, you’ll help set technical direction and shape the long-term architecture of our backend services while still being hands-on with coding and delivery. You will collaborate across engineering, product, design, and other stakeholders to ensure scalable, reliable, and impactful systems that power consumer experiences, partner integrations, and our core business platforms. You’ll also play a critical role in mentoring engineers, elevating technical standards, and ensuring the success of projects end-to-end.

Our Engineering Teams

• Consumer Engineering: Builds the APIs and backend systems powering Flex’s main consumer-facing products. This team focuses on delivering scalable services for a seamless rent payment experience through our mobile and web apps.
  
  
• Partner Integrations Engineering: Owns the backend services and integrations that connect Flex to financial partners and payment networks, ensuring reliable, secure payment flows and partner-facing experiences.
  
  
• Core Platform Engineering: Maintains the backend systems and infrastructure supporting all business features, including Payments, Billing, Identity, and Partner Integrations, ensuring Flex’s foundation is robust and scalable.
  
  
• Risk Platform Engineering: Develops the platforms and APIs that mitigate credit and fraud risk, enhancing customer accessibility while safeguarding against misuse through advanced rules engines, machine learning, and event data systems.

What You’ll Do

• Design, implement and maintain our Finance service and internal tooling, including financial reporting, reconciliation/audit process.
• Design and develop new APIs and functionalities to support large money movements across our banking partners via different payment rails, such ACH.
• Scale out core platform to support business growth while maintaining performance and reliability 
• Continuously improving our daily operations with automation, tooling, design evolution, observability etc.
• Work closely with product, analytics, finance and engineering peers to launch new financial features into our platform

What We're Looking For

• 6+ years of experience in software development or a related field 
• Experience in technical leadership, guiding engineering teams through complex projects 
• Experience with Java, Python, Golang, or TypeScript/Node.js.
• Strong experience with relational SQL and NoSQL databases, such as MySQL/PostgreSQL/DynamoDB
• Experience in designing and developing the fault-tolerant and scalable distributed systems 
• Experience with AWS cloud services: ESC/EKS, Lambda, API Gateway, VPN, RDS etc
• Infrastructure as code(AWS CLI, AWS CDK/Terraform)  
• Strong communication skills with the ability to understand and explain technical issues to a non-technical audience 
• Follow engineering best practices as well as propose new ones 
• Experience with finance reporting and reconciliation
• Deep experience with writing complex query and data mining
  
  

• Tier A: (NYC/SF): $200,000 —$250,000 USD
• Tier B: $180,000—$225,000 USD
• Tier C: $170,000 —$212,500 USD

#LI-Remote

The Role:

Visa sponsorship is not offered for this role.

Learn More about Value Engineering at Celonis Here

About the Role:

The Machine Learning team at Tubi drives the innovation behind personalized user experiences.  With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming.

We are seeking a highly skilled Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions.

What You'll Do:

• Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience
• Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas
• Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
• Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences.
• Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement

Your Background:

• 8+ years of industry experience building production Machine Learning systems
• MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field
• Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
• Proficiency in building and deploying full-stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
• Solid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning.
• Ability to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutions.

#LI-Hybrid #LI-SC1

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

Role Description

• As a Senior Value Engineer specializing in Healthcare Distribution and Logistics, you are pushing the envelope in solving business-critical problems for one of the world's largest healthcare wholesale and distribution enterprises. You will be working intimately with this strategic client, understanding their uniquely complex objectives—spanning from high-volume warehouse optimization and pharmacy fulfillment to ensuring seamless hospital supply logistics and DSCSA compliance—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customer's massive, high-velocity distribution network. This enables them to industrialize AI, unlocking real ROI on deployments at scale, and ultimately ensuring critical medicines and medical supplies reach care providers and patients without delay. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Supply Chain SVPs and logistics leaders, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis within this premier healthcare distribution network.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the client's overarching AI strategy and the distinct supply chain challenges inherent to healthcare wholesale (e.g., predictive demand forecasting for generic and brand pharmaceuticals, optimizing distribution center throughput, navigating complex contract pricing, or managing acute care logistics). As a Celonis product and distribution domain expert, translate these high-volume logistics requirements into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle across various distribution and operational business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached in both corporate and warehouse environments.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and fulfillment networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, procurement, and customer service.

• Agentic Process Transformation: Support the client in achieving tangible ROI from AI at an enterprise scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous resolution of order-to-cash disputes, intelligent backorder handling, or automated warehouse exception management).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs, Warehouse Management Systems (WMS), Transportation Management Systems (TMS), and strict regulatory track-and-trace frameworks (e.g., DSCSA).

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for Healthcare Distribution, scaling knowledge across the organization regarding the nuances of medical/surgical and pharmaceutical wholesale operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, Logistics, or Wholesale Distribution environments (Healthcare/Pharma distribution preferred). This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume distribution (such as Order-to-Cash, Procure-to-Pay, Inventory Management, Warehouse Operations, or Transportation Logistics) with the ability to translate high-level operational needs into specific 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., intelligent chatbots for pharmacy/hospital customer support, or automated extraction of data from complex vendor contracts and rebate agreements).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional supply chain datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, warehouse directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, 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 suited for highly regulated healthcare logistics environments.

• Familiarity with distribution-specific systems and standards (e.g., Manhattan, Blue Yonder, SAP EWM, and DSCSA track-and-trace serialization data).

• 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).

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

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

Role Description

• As a Senior Value Engineering Consultant 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

About the Role

As a Technical Deployment Lead on the Claude Agentic Solutions team, you will lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries. You'll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes.

This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion. You will champion our mission in the field, ensure world class delivery, and bring insights back to our product and research teams on a regular basis.

You'll own engagements end-to-end, from SOW through production deployment. You'll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organizational complexity that comes with deploying AI agents in enterprise environments. You need to be technical enough to hold architecture conversations with engineering stakeholders and polished enough to run executive briefings with C-suite sponsors.

Responsibilities

• Own the technical delivery plan for each engagement. Structure SOWs with clear scope, milestones, dependencies, success criteria, and value hypotheses. Translate customer business objectives into a sequenced roadmap that FDEs execute against.
• Lead technical discovery. Map customer workflows, identify constraints, define MVP scope, and shape the solution architecture for custom agent deployments.
• Run day-to-day engineering execution. Drive delivery across Anthropic and customer teams. Keep progress unblocked and sequenced. Make real-time trade-offs on scope and priority to protect the critical path.
• Own product scoping for field engagements. Define the MVP, author requirements documentation, prioritize the engineering backlog, and manage scope against success criteria as requirements evolve.
• Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent Anthropic's technical credibility with senior business and engineering leaders.
• Own value measurement and ROI. Define impact hypotheses, set baselines and KPIs, run pre- and post-deployment measurement, and report outcomes to executive sponsors.
• Codify reusable delivery assets. Build solution patterns, evaluation frameworks, and technical playbooks. Extract what works across engagements and feed field signals back to Product and Research to improve our platform and models.
• Navigate enterprise and regulatory complexity. Security reviews, legal approvals, procurement processes, compliance requirements, and organizational dynamics.
• Manage scope and change. Handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and escalate with clear context when needed.
• Run delivery operations. Sprint ceremonies, milestone reviews, and progress reporting.
• Travel to customer sites. Build relationships, unblock delivery, and accelerate adoption. (25–50% expected).

You May Be a Good Fit If You

• Have led AI/ML engagements/deployments, whether as a founder, data scientist, engineer, researcher, or in a professional services or consulting role.
• Have delivered AI, ML, or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.
• Have experience in a specialized vertical (financial services, life sciences, pharmaceutical, retail, mining, agriculture, etc.).
• Can lead architecture discussions with engineering stakeholders, evaluate technical trade-offs, and pressure-test technical decisions. You won't write production code, but you will own the technical direction of engagements alongside FDEs.
• Have a track record delivering complex, high-stakes technical projects for enterprise clients where outcomes depended on tight coordination and fast decision-making — ideally across multiple workstreams in regulated industries.
• Have executive presence — polished, credible, and comfortable representing Anthropic to senior leaders in high-stakes environments.
• Thrive in ambiguity and bring structure where none exists.
• Have a builder's mindset — you're here to create a function, not join one.

Role Description

• As an 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

Current is a leading consumer fintech platform transforming financial access for everyday Americans with over 6 million members. We provide access to financial solutions that seamlessly work together to solve the needs of our members and enable all Americans to build better financial futures. Based in NYC, our results-driven environment drives us to build better products, grow faster and empower everyone on our team to have an impact on our business and mission to improve financial outcomes.

Current’s Engineering team is dedicated to building our products and infrastructure. With our applications running on Google Cloud Kubernetes Engine, we support a proprietary banking core that can scale to handle millions of transactions a day. Our stack includes MongoDB and Spanner for persistence, Pub/Sub for asynchronous event processing, Dataflow for data transformation paired with BigQuery and Google Cloud Storage for data storage and analytics. Our backend services are written in Java and our data pipelines are built in Scala.

We work across a broad set of domains, including user-facing products like liquidity offerings and reward programs, infrastructure for machine learning and experimentation, real-time fraud detection and identity protection, and large-scale transaction processing across multiple payment rails.

About the Role

We're looking for a Senior Software Engineer to join our team and apply ML/AI techniques to solve business problems at scale. You'll find creative ways to apply ML where it can move the needle, leverage existing tooling and frameworks, and ship production solutions that deliver measurable impact. The ideal candidate is a strong backend engineer with hands-on ML experience who thrives on turning business problems into production ML solutions. This role has a salary range of $200,000 - $250,000.

What You'll Work On

Our work spans many areas, and here are a few examples of active problem spaces:

• Predictive models for user conversion that directly reduce acquisition costs
• Mining customer and transaction data to surface insights that shape product strategy
• Applying LLMs creatively to interpret customer behavior and make sense of unstructured data
• Real-time fraud detection, identity protection, and transaction decisioning

Responsibilities

• Owning end-to-end delivery of ML-powered initiatives from problem discovery through system design to production launch
• Building and evolving systems across the backend and ML stack, from microservices and data pipelines to feature engineering and model tooling
• Evolving org-wide engineering standards for architecture, testing, and monitoring practices and documentation
• Mentoring engineers through code and architecture reviews, raising the technical bar of the team
• Partnering with data science, product engineering, and infrastructure teams to shape the data and ML strategy and drive adoption of ML solutions across products

Required Qualifications

• 5+ years of software engineering experience, with backend experience using a JVM language, preferably Java
• 2+ years of building and deploying ML models in production
• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
• Solid understanding of algorithms, data structures and object-oriented design
• Experience with cloud-hosted services, like AWS or GCP
• Experience with relational and NoSQL databases
• Experience working closely with data science and infrastructure teams
• Strong problem-solving and communication skills

Nice-to-Have Qualifications

• Experience with Scala or Python
• Hands-on experience applying LLMs or other AI tooling to production use cases
• Exposure to ML platforms such as SageMaker, Vertex AI, or Kubeflow

Benefits

• Competitive salary
• Meaningful equity in the form of stock options
• 401(k) plan
• Discretionary performance bonus program
• Biannual performance reviews
• Medical, Dental and Vision premiums covered at 100% for you and your dependents
• Flexible time off and paid holidays
• Generous parental leave policy
• Commuter benefits
• Fitness benefits
• Healthcare and Dependent care FSA benefit
• Employee Assistance Programs focused on mental health
• Healthcare advocacy program for all employees
• Access to mental health apps
• Team building activities
• Our modern Chelsea-based office with open floor plan, stocked kitchen, and catered lunches

The Team: Global Value Engineering Center of Excellence

Become an integral part of our international, diverse, and dynamic Global Value Engineering Center of Excellence. Our Value Engineers are trusted advisors who operate at the intersection of technology and business, partnering with sales and customers to develop compelling Celonis-powered solutions and prototypes that address critical business challenges.

We foster a fast-paced, collaborative environment built on trust, continuous learning, and mutual growth through coaching and mentorship.

The Role: Launch Your Enterprise Software Career

Kickstart your career in enterprise software through our immersive 12-month Orbit Program. This program offers a unique blend of client engagements, dedicated mentorship, and a strong team culture where collaboration and shared success are paramount. You'll leverage your technical background to develop essential Value Engineering skills, build lasting client relationships, and establish yourself as a trusted advisor, paving the way for significant career growth within Celonis.

The Orbit Program is structured into classes and cohorts, with start dates organized twice a year. You'll likely join a cohort with a summer start date (June/July) or a winter start date (January/February), allowing you to grow and develop alongside your cohort peers.

Your journey begins with comprehensive onboarding and enablement, followed by hands-on experience in customer engagements and targeted training. You will gain expertise in:

• Building and coding within the Celonis platform (SQL and PQL)
• Scoping business and technical requirements
• Effectively handling objections
• Developing industry domain knowledge
• Delivering impactful presentations and demos
• Understanding value selling and realization
• Managing customer accounts

What You'll Do:

• Consult with customers using systems analysis to identify core business challenges and determine how Celonis can drive impactful solutions.
• Present the Celonis AI value proposition and vision to customers and align our solutions with their AI strategy.
• Prototype and develop AI solutions tailored to customer needs, including both traditional machine learning and LLM-based solutions.
• Execute proof projects showcasing the value of Celonis Process Intelligence in the context of our customers’ strategy, business initiatives, and challenges
• Develop and modify Celonis data models using SQL and analyses using PQL (Celonis proprietary language) to create compelling prototypes that address customer pain points.
• Lead proof-of-concept projects within the Celonis platform to demonstrate tangible value aligned with customer strategies and needs.
• Collaborate with customers and partners to design and build Celonis solutions that ensure a positive return on investment.
• Establish strong, trusted advisor relationships with customers through your technical expertise, product knowledge, and business acumen.

Articulate and quantify strategic business value for customers, delivering impactful presentations to senior executives.

• Partner with the implementation services team to ensure successful value realization for customers.
• Identify opportunities for innovation and collaborate with Product & Engineering teams to influence future product development.
• Contribute to the Global Value Engineering Center of Excellence by creating reusable collateral, best practices, and tools.

What You Need:

• Bachelor’s degree in Business, Engineering, Data Analytics, Economics, Computer Science, Mathematics, or a related STEM field.
• Extensive internship experience or 1-3 years of full-time work experience.
• Hands-on experience with at least one of the following: SQL, Microsoft Power BI, Tableau, or another data analytics solution.
• A strong passion for technology, big data, and its transformative potential.
• Excellent analytical and creative problem-solving skills, with the ability to apply technology to business challenges.
• A customer-centric mindset with a focus on delivering value.
• The ability to build relationships with senior management and influence decision-making.
• Confidence in presenting to diverse audiences.
• A proactive approach to problem-solving, with a willingness to learn from mistakes.
• Curiosity, self-motivation, a commitment to continuous learning, and the desire to thrive in a fast-paced, high-growth environment.
• Strong organizational skills with the ability to prioritize and execute on deadlines.
• Excellent communication skills and fluency in English.

Bonus Points:

• GPA of 3.6 or higher.
• Degree in Industrial Engineering or a similar field.
• Degrees combining technical (e.g., Computer Science, Data Science) and business (e.g., Economics, Marketing) skills.
• Experience with Python and Machine Learning.
• Customer-facing, customer success/service, or sales experience.
• Experience with Proof of Concept projects.
• Supply Chain process experience (Procurement, Order Management, Inventory Management, Production).
• Finance process experience (Accounts Payable, Accounts Receivable).
• Experience modeling ROI and TCO for business case justification.
• Experience with SAP and/or Oracle.
• Fluency in French and/or Spanish.

Visa sponsorship is not offered for this role.