- Company Name
- Syngenta Group
- Job Title
- AI Solution Architect for Commercial
- Job Description
-
Job title: AI Solution Architect for Commercial
Role Summary: Lead the design, architecture, and delivery of large‑scale AI/ML solutions that integrate generative AI with enterprise platforms such as Salesforce, AWS, and Databricks. Drive MLOps practices, cost optimization, and regulatory compliance while translating business objectives into technical blueprints and steering cross‑functional teams.
Expactations: Deliver scalable, secure, and compliant AI systems that meet commercial objectives. Own end‑to‑end solution design, from data engineering to deployment, and provide strategic guidance to senior stakeholders. Ensure adherence to AI governance, security standards, and ROI expectations.
Key Responsibilities:
- Design and implement enterprise AI architectures integrating Salesforce, AWS SageMaker, Databricks, and other critical systems.
- Build and maintain ML infrastructure, including SageMaker Pipelines, Databricks notebooks, Delta Lake, and Spark clusters.
- Architect autonomous AI solutions using LangChain, LlamaIndex, AutoGPT, and custom Agentforce/N8N integrations.
- Develop cross‑environment authentication and security frameworks that meet enterprise AI security and Shield Platform Encryption requirements.
- Establish MLOps pipelines (CI/CD, model registry, feature store) and govern model lifecycle, compliance, and governance.
- Monitor and manage AI infrastructure costs, providing cost models and optimization strategies.
- Lead architecture reviews, technical decision‑making, and translate technical concepts for C‑level stakeholders.
- Foster cross‑functional collaboration among 5–15 engineers, data scientists, and architects.
Required Skills:
- Expertise in enterprise AI/ML architecture (SageMaker, Databricks, AWS Bedrock).
- Hands‑on experience with large language models, generative AI, fine‑tuning, and LLM deployment.
- Advanced knowledge of MLOps, CI/CD for AI, model registry, and feature store implementation.
- Strong data engineering skills: Delta Lake, Spark optimization, streaming architecture.
- Deep Salesforce architecture experience (multi‑org, data model, Shield Security).
- Proficiency in prompt engineering, RAG, vector databases, and LLM safety testing.
- Ability to design and enforce AI technical blueprints and compliance frameworks.
- Leadership skills: translating technical solutions to business ROI, managing cross‑functional teams, and influencing C‑level stakeholders.
Required Education & Certifications:
- Master’s or PhD in Computer Science, AI/ML, Data Science, or related field (or Bachelor’s with extensive relevant industry experience).
- Certifications in AWS (e.g., AWS Certified Machine Learning – Specialty), Databricks Academy, and Salesforce Architecture Certifications are preferred.
Manchester, United kingdom
On site
13-01-2026