Xylem
Website:
xylem.com
Job details:
This role works globally across sustainability, product engineering, manufacturing, sourcing, product management and digital teams. It requires strong technical judgment, ownership and the ability to translate complex environmental results into practical product decisions.
What You Will Deliver
• Independently plan and complete cradle-to-gate and cradle-to-grave LCAs for hard industrial products and product families in accordance with applicable standards, product category rules and program instructions.
• Own EPD development from scoping and PCR selection through background report, declaration content, evidence package, independent verification responses and publication support.
• Build reusable product-family models, parameterized assumptions, data-collection templates, quality controls and documentation that increase team throughput without weakening methodological integrity.
• Create and deploy governed AI-enabled workflows that reduce manual effort and improve consistency across LCA and EPD delivery.
• Identify environmental hotspots and translate findings into clear recommendations for engineering, sourcing, operations and product strategy.
• Mentor colleagues and improve team practices through guidance, training, templates and lessons learned.
Key Responsibilities
LCA, Product Carbon Footprint and EPD Delivery
- Define goal and scope, functional or declared unit, system boundaries, allocation rules, scenarios, cut-off criteria, data-quality requirements, sensitivity analyses and interpretation approach.
- Collect, reconcile, validate and document primary and secondary data from BOMs, drawings, ERP records, suppliers, manufacturing sites, test data, service information and engineering experts.
- Model materials and processes relevant to industrial equipment, including metals and castings, machining, motors and drives, electronics, assembly, packaging, transport, product use, maintenance, lifetime and end-of-life.
- Apply ISO 14040 and ISO 14044 and as relevant to the deliverable, ISO 14025, ISO 14067, EN 15804, ISO 21930, applicable PCRs and EPD program-operator rules.
- Use SimaPro as the preferred LCA platform and work effectively with relevant databases and complementary LCA tools.
- Prepare transparent technical documentation, assumptions logs, data-quality assessments, calculation records, LCA reports, EPD drafts and verifier response files.
- Conduct peer reviews and quality checks to ensure reproducibility, consistency, traceability, and audit readiness.
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Generative and Agentic AI Enablement
- Design, test and operationalize repeatable AI-assisted workflows using enterprise-approved tools such as Microsoft 365 Copilot, Copilot Studio, or equivalent platforms.
- Use AI effectively for activities such as structured data-request preparation, document and evidence review, controlled extraction, source comparison, gap identification, drafting, consistency checks, knowledge retrieval, meeting follow-up, and workflow orchestration.
- Create reusable prompt patterns, agent instructions, evaluation criteria, human-review checkpoints, and operating guidance for LCA and EPD use cases.
- Measure and communicate the benefit of AI-enabled use cases, including cycle-time reduction, rework avoided, quality improvement, adoption, and additional delivery capacity.
- Apply responsible AI and information-governance requirements, including confidentiality, access control, source citation, version control, validation, and documented human accountability.
- Prevent unsupported AI-generated assumptions or data from entering LCA models or externally verified deliverables. Ensure every material input and claim remains traceable to an approved source or documented expert judgment.
- Partner with digital specialists when technical integration is needed. Coding is not a core requirement for this role.
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Collaboration and Capability Building
- Work with global product teams to define data needs, resolve gaps, and embed product sustainability evidence into development and decision-making.
- Provide practical guidance on LCA methodology, EPD requirements, data quality, use-phase assumptions, and environmental claims.
- Train and coach team members in LCA methods, quality practices and safe, effective AI adoption.
- Contribute to standard methods, model libraries, digital work instructions, controlled knowledge bases and continuous-improvement initiatives.
- Communicate clearly with technical and non-technical stakeholders across cultures and time zones.
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Required Qualifications and Experience
- Bachelor's or Master's degree in environmental, mechanical, chemical, industrial, or manufacturing engineering; sustainability; environmental science; or a closely related field.
- 5+ years of relevant experience in product LCA, product carbon footprinting, EPD development, or industrial product sustainability, with the maturity to own work independently.
- Demonstrated completion of multiple end-to-end product LCAs. Experience with at least one EPD or comparable externally reviewed product declaration, including verifier or reviewer interaction, is strongly expected.
- Advanced working knowledge of ISO 14040 and ISO 14044, plus practical knowledge of EPD and product-carbon-footprint requirements.
- Proficiency with SimaPro preferred. Strong experience with another established LCA platform may be considered when accompanied by evidence of rapid tool adaptability.
- Practical understanding of BOMs, manufacturing processes, supplier data, engineering specifications, use-phase modeling, data-quality assessment, uncertainty and sensitivity analysis.
- Advanced Excel capability for structured data preparation, reconciliation, quality checks, and transparent calculations.
- Strong written and spoken English, stakeholder management, technical writing and the ability to manage several deliverables with disciplined documentation.
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Required AI Practitioner Evidence
Candidates should provide evidence of applied capability, not only personal experimentation or awareness. Evidence may include:
- A portfolio or clear description of at least two delivered Generative AI or agentic AI use cases that improved a real business or technical workflow.
- Explanation of the problem, workflow design, tools used, human controls, information-security considerations, evaluation method, user adoption and measurable result.
- Demonstrated skill in prompt and context design, grounded retrieval from controlled sources, output evaluation, hallucination risk management and workflow documentation.
- At least one relevant credential, structured learning program, employer-recognized qualification, or equivalent demonstrable professional development in Generative AI, agentic AI, Microsoft Copilot, responsible AI, or AI-enabled business-process improvement.
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Preferred Qualifications
- Experience with pumps, wastewater equipment, rotating equipment, motors, drives, valves, treatment systems, or comparable engineered industrial products.
- Experience creating product-family or parameterized LCA models and reducing effort across product variants.
- Experience with EPD program operators, PCR interpretation, independent verification, and publication processes in more than one region.
- Familiarity with SAP or another ERP, PLM/PDM systems, supplier-data workflows, Power BI, Power Automate, Power Apps, Copilot Studio, or similar low-code tools.
- Experience supporting eco-design, sustainable procurement, environmental claims, product compliance, or customer sustainability requests.
- Python, SQL, APIs, or software development experience is welcome but not required.
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How Success Will Be Measured
- On-time completion and successful review or verification of assigned LCA, PCF, and EPD deliverables.
- Increased team capacity and shorter delivery cycle time while maintaining or improving quality.
- Reuse of verified models, datasets, templates, prompts, agents and documented workflows across products and teams.
- Reduction in data gaps, rework, inconsistent assumptions, and verifier comments.
- Adoption of governed AI-enabled practices by the wider team, supported by clear controls and measurable benefits.
- Actionable insights that influence product design, sourcing, manufacturing, service, or portfolio decisions
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