SATIC: Forward -Deployed Engineer at PricewaterhouseCoopers (PwC)

About the Agentic Innovation Lab The Innovation Lab serves as SATIC’s AI engineering hub. It focuses on solving complex business problems by designing, building, and scaling AI-powered solutions (Generative AI, Agentic AI, and intelligent automation) to transform business operations. 
The Role

• This position sits at the intersection of legal domain expertise and applied AI engineering. The role is "forward-deployed", meaning the engineer embeds directly with client teams to diagnose bottlenecks, map workflows, and build solutions within the client’s environment. Between deployments, the engineer works from the Innovation Lab to refine internal tools and contribute to a reusable asset library. 

Key responsibilities 

• Solution Architecture and AI Engineering Deconstruct workflows into machine-readable logic; Build RAG pipelines (embedding models, vector databases, retrieval tuning); Architect multi-agent systems; and Maintain taxonomies and metadata schemas.
• Engineering, Prototyping & Production Delivery Rapidly iterate AI prototypes; Integrate AI with enterprise platforms (CLM, document repositories, APIs); and Establish evaluation frameworks for accuracy, latency, and cost.
• Client Engagement & Forward Deployment Embed on-site for 2–6-week sprints; Manage concurrent engagements; Act as a technical translator between stakeholders and engineering teams; and Deliver technical demonstrations.
• Risk, Governance & Quality Assurance Implement guardrails against hallucinations and bias; Ensure compliance with data privacy (GDPR, POPIA) and AI governance frameworks (EU AI Act, ISO/IEC 42001, NIST AI RMF); and Maintain audit trails.
• Team Contribution & Knowledge Building Manage technical backlogs (Jira/Azure DevOps); Mentoring junior associates; and Contribute to the shared asset library. 
• Experience & Skills 

Domain Expertise

• Bachelor’s degree (Economics, Law, Computer Science, Data Science, Information Systems, or equivalent); 4–5 years of experience in Business Engineering, Operations, or Product Development;
• Ability to map complex business processes. Engineering and AI Experience with at least one LLM orchestration framework.
• Working knowledge of at least one major cloud platform. Experience integrating AI solutions with enterprise systems.
• CommunicationAbility to explain technical AI concepts to business professionals and deliver polished demonstrations to senior stakeholders. 

Desired Skillsets

• Experience with AI evaluation and observability tools. 
• Hands-on configuration experience with CLM platforms or workflow automation tools Familiarity with AI governance frameworks: EU AI Act risk classification, ISO/IEC 42001, NIST AI RMF, or responsible AI principles.
• Experience with fine-tuning LLMs, training custom embedding models, or building custom evaluation datasets. Solid understanding of Agile/Scrum delivery and legal professional privilege. 
• Soft skills and innovation mindset Builder Instinct: 
• Prioritizes functional prototypes while maintaining good documentation.
• Comfort with Ambiguity: Capable of creating structure in uncertain environments. Rigorous and Precise: Disciplined in testing and ensuring accuracy in enterprise AI. Collaborative: Values cross-functional input and team effectiveness. Intellectually Honest: Transparent about knowledge gaps and collaborative in seeking help.

Requirements added by the job poster

• 2+ years of work experience with Microsoft Excel