Transformational consultant at Sicredi integrating AI with agile practices for sustainable business solutions. Engaging in innovation and project management to deliver strategic business impact.
About the role
- Lead the enterprise GenAI strategy and multi-year roadmap; bring sustainable methodologies (evals, safety, cost/perf, lifecycle).
- Design, prototype, and ship AI agents/RAG/search, document automation, knowledge assistants, and workflow copilots tied to measurable outcomes.
- Pressure-test external solutions for explainability, sustainability, and model-evolution roadmaps; recommend build vs. buy.
- Partner with IT on platform choice and reference architectures (vector DB, policy/guardrails, observability, prompt/eval stores); guide design for internally built solutions.
- Assist business owners with AI procurement—lead technical due diligence, security/compliance feasibility, and integration planning with commercial and IT.
- Oversee the architecture, design, and deployment of AI/ML solutions across the enterprise with emphasis on:
- Deep learning (CNNs, RNNs, transformers, attention-based architectures)
- Generative AI and LLMs (OpenAI, Anthropic, Azure/OpenAI Service, Hugging Face)
- Predictive and prescriptive analytics (time series forecasting, anomaly detection, optimization)
- Computer vision and NLP for enterprise use cases (quality inspection, document intelligence, conversational AI)
- Drive enterprise-grade integration of GenAI into business workflows by connecting LLMs to internal knowledge repositories and systems (RAG, agent frameworks, secure APIs).
- Build scalable AI infrastructure and pipelines with CI/CD for ML models.
- Implement monitoring, drift detection, retraining, and explainability frameworks.
- Leverage cloud AI/ML platforms (Azure ML, AWS Sagemaker, GCP Vertex AI) for enterprise deployments.
- Partner with R&D, supply chain, manufacturing, customer operations, and IT to embed AI into core business systems and products.
- Ensure availability of high-quality, governed data pipelines (ETL/ELT, feature stores, vector databases).
Requirements
- Bachelor’s (12+ yrs), Master’s (10+ yrs) relevant experience.
- Proven success deploying GenAI in commercial or enterprise settings and scaling from pilot to production.
- Hands-on experience building AI agents/RAG with strong Python; practical LLM ops (prompting, evals, guardrails, cost/perf tuning).
- Deep enterprise integration experience (REST, webhooks, eventing) and connecting AI to core ERP/CRM/MES/DWH/SaaS platforms.
- Excellent communicator who simplifies complexity and navigates cross-functional stakeholders (execs → frontline).
- Strong analytical mindset—defines success metrics, measures outcomes, and iterates.
- Governance experience: policy frameworks, DPIA/PIA, export controls, data residency (incl. China), model risk.
- Manufacturing/semiconductor background; familiarity with Oracle EBS, Salesforce, Opcenter/Camstar, ServiceNow, Snowflake/Databricks.
- Experience evaluating third-party AI (e.g., Microsoft Copilot/Azure OpenAI, Glean/Moveworks, AWS Bedrock) and negotiating vendor SOWs.
- Change-management frameworks; ability to craft AI literacy and enablement programs.
Benefits
- Hybrid position (three days a week in office)
- Working conditions are those typically found in an office, corporate environment.
- Physical requirements are those typically associated with a professional role - sitting, computer and accessories use.
- All employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards.
- Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System.
- Ensure adherence to company’s values (ICARE) in all aspects of your position at Coherent Corp.
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