Senior Applied Value Engineer - UKI Energy, Oil & Gas

NextGenEnergyJobs; Bengaluru; Hybrid; INR 4,500,000 - 6,000,000; Full time

Job summary

NextGenEnergyJobs in Bengaluru seeks a Senior Applied Value Engineer to drive AI strategy discussions, translate business needs into AI use cases, and lead prototyping with cutting-edge technologies.

You will organize proof-of-value projects, ensure robust architecture, and guide customers through scalable LLM/agent deployments with governance and security considerations.

Qualifications

• 6+ years of experience leading technical pre-sales, including defining AI roadmaps and ROI/TCO business cases.

Responsibilities

• Understand customers AI strategy and translate requirements into AI solutions.
• Lead prototyping and hackathons to rapidly demonstrate value.
• Support customers in achieving ROI from AI deployments at scale.

Skills

Python

LangChain

pandas

pydantic

sklearn

PyTorch

Machine Learning

Generative AI

Pre-sales

Education

Bachelor's Degree

Master's Degree in CS/ Engineering/ Mathematics

Tools

LangChain

LlamaIndex

AWS Bedrock

Azure AI

GCP Vertex

Job description

As an Senior Applied Value Engineer you push the envelope in solving mission-critical problems for our customers.

Key Responsibilities

• 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
• 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
• 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
• 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.
• Ensure Successful Project Outcome: Senior Applied Value Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Senior Applied Value Engineer specialize in domains (e.g. supply chain) and industries

Requirements

• 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, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.
• 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)