SATIC: Forward -Deployed engineer

PwC South Africa; Wes-Kaap; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

PwC South Africa's Technology & Innovation Centre (SATIC) invites an experienced AI engineer to join the Agentic Innovation Lab. You will work forward-deployed with client teams to diagnose bottlenecks, map workflows, and build scalable AI-powered solutions in real environments.

You will refine internal tools, mentor juniors, manage backlogs, and contribute to a reusable asset library, while upholding data privacy, governance, and quality standards.

Qualifications

• Bachelor's degree or higher in a relevant field.
• 4–5 years of experience in Business Engineering, Operations, or Product Development.
• Ability to map complex business processes.

Responsibilities

• Solution Architecture and AI Engineering: deconstruct workflows and build multi-agent systems.
• Client Engagement & Forward Deployment: embed on-site for 2–6 week sprints and deliver demonstrations.
• Risk, Governance & Quality Assurance: implement guardrails and ensure data privacy compliance.
• Team Contribution & Knowledge Building: mentor juniors and contribute to shared assets.

Skills

LLM orchestration

Cloud platforms

Enterprise AI integration

Stakeholder communication

Education

Bachelor's degree (Economics, Law, CS, Data Science, IS)

Job description

South African Technology & Innovation Centre (SATIC) is the latest part of PwC, a global brand delivering services for the biggest clients in the world. PwC leads the way in human led, technology enabled professional services, working with clients to transform their business and make it fit for the future. We are looking for candidates who bring in-depth market experience, who see technology as a way to enable and drive human innovation and who want to be a part of a community of solvers, to tackle the biggest challenges in society.

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

1. Solution Architecture and AI Engineering

• Deconstruct workflows into machine-readable logic;
• Build RAG pipelines (embedding models, vector databases, retrieval tuning);
• Architect multi-agent systems;
• Maintain taxonomies and metadata schemas.

• Rapidly iterate AI prototypes;
• Integrate AI with enterprise platforms (CLM, document repositories, APIs);
• Establish evaluation frameworks for accuracy, latency, and cost.

3. 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;
• Deliver technical demonstrations.

4. 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);
• Maintain audit trails.

5. Team Contribution & Knowledge Building

• Manage technical backlogs (Jira/Azure DevOps);
• Mentoring junior associates;
• 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.

Communication

• Ability 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.