Senior Applied Value Engineer – Automotive Manufacturing

Senior Applied Value Engineer – Automotive Manufacturing

Role Description

As a Senior Applied Value Engineer, you will push the envelope in solving business-critical problems for strategic customers within our Automotive Manufacturing Vertical. You will partner with our most important clients to understand their unique objectives—from supply chain transformation and warranty management to large-scale cost-takeout programs. By combining the world’s leading Process Intelligence (PI) platform with technologies from top AI and ML partners (Microsoft, OpenAI, Databricks), you will build innovative solutions that drive measurable impact.

Using our PI platform, we feed operational context to AI, bridging IT and OT systems so it understands our customers’ complex business realities. This enables them to industrialize AI and unlock real ROI at scale. You will prototype these solutions, demonstrate their value to automotive and manufacturing executives, and ensure successful implementation, adoption, and value realization to expand our footprint across the global automotive landscape.

Key Responsibilities

• AI Discovery & Solutioning: Understand customers' AI strategies and sector-specific challenges (e.g., predictive maintenance, supply chain resilience, quality management). Find the best problem-solution fit and translate customer requirements into innovative, needle-moving solutions.

• Pre- and Post-Sales Execution: Drive the full customer lifecycle. Lead technical discovery and capability demonstrations during pre-sales, and remain deeply involved post-sale to guide implementation and ensure agreed value and adoption thresholds are met.

• Hackathons & Prototyping: Leverage cutting-edge AI technologies to rapidly build creative prototypes during customer hackathons. Solve critical pain points specific to supply chain, manufacturing, and warranty/quality with a proactive, "can-do" approach.

• Agentic Process Transformation: Shift customers from traditional, rule-based automation to autonomous AI agents empowered by Process Intelligence (e.g., intelligent production scheduling, autonomous procurement), ensuring real ROI on AI deployments.

• Proof Projects: Architect and execute business-critical Proof-of-Value projects. Deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, integrating seamlessly with enterprise data, identity protocols, and stringent manufacturing compliance frameworks.

• Domain & Industry Leadership: Serve as the primary technical subject matter expert for the automotive manufacturing sector. Scale deep domain expertise across the organization to deliver high-value solutions for OEMs and Tier-1 suppliers.

• Smart Factory & Assembly Automation: Champion Industry 4.0 initiatives. Specialize in assembly line automation, robotics, predictive maintenance, Industrial IoT (IIoT), and discrete manufacturing workflows for high-volume production.

• EV & Advanced Vehicle Production: Act as a technical advisor on the transition to Electric Vehicles (EVs) and Software-Defined Vehicles (SDVs). Optimize battery production lines, connected factory ecosystems, and complex OEM/Tier-1 dynamics.

• Sustainable Production & Factory Energy: Drive technical strategy for energy-efficient plant operations. Focus on integrating renewable energy into factory power grids and optimizing utility usage across the vehicle production lifecycle.

Requirements

• Experience: 4+ years leading end-to-end technical pre-sales and post-sales engagements within manufacturing and production. Proven ability to define AI roadmaps, build compelling ROI/TCO business cases, and guide technical implementations to value realization.

• Domain Expertise: Deep understanding of manufacturing business processes. In-depth experience in domains such as Asset Management, Supply Chain, Quality Control, or Capital Projects, with the ability to translate strategic requirements into impactful solutions.

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

• Communication Skills: Strong presentation and storytelling skills for both internal and external stakeholders (C-level executives and operational leaders), capable of leading technical whiteboarding sessions, formal readouts, and live demos.

• Education: Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or a related field (or equivalent work experience) preferred.

Nice to Have

• Agentic Systems: Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, with rigorous evaluations for highly regulated industries.

• LLM Ecosystem: Working knowledge of OSS packages like LangChain or LlamaIndex.

• Cloud & IoT: Experience 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.

• Generative AI: Expertise in GenAI techniques (RAG, few-shot learning, multi-agent orchestration, multimodal understanding, fine-tuning) to build high-impact use cases like automated engineering document processing or intelligent diagnostic chatbots.

Sponsorship is not available for this role.