PwC South Africa
2 weeks ago
SATIC: Forward - Deployed Engineer
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Company information
- Company
- PwC South Africa
- Location
- South Africa, Western Cape, Cape Town Region, Cape Town City Centre South Africa
- Posted
- 2 weeks ago
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 LabThe 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 RoleThis 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 responsibilities1. 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.
- Embed on-site for 2–6-week sprints
- Manage concurrent engagements
- Act as a technical translator between stakeholders and engineering teams
- Deliver technical demonstrations.
- 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.
- Manage technical backlogs (Jira/Azure DevOps)
- Mentoring junior associates
- Contribute to the shared asset library.
- 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.
- Experience with at least one LLM orchestration framework
- Working knowledge of at least one major cloud platform
- Experience integrating AI solutions with enterprise systems.
- Ability to explain technical AI concepts to business professionals and deliver polished demonstrations to senior stakeholders.
- 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.
- 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.
Required skills
- product development
- operations
- jira
- generative ai
- scrum
- agile
- gdpr
- vector databases
- apis
- azure devops
- observability tools
- workflow automation
- agentic ai
- llms
- business engineering
- intelligent automation
- rag pipelines
- ai engineering
- popia
- responsible ai
- cloud platform
- clm
- embedding models
- enterprise platforms
- eu ai act
- ai evaluation
- iso/iec 42001
- nist ai rmf
- llm orchestration framework
- legal professional privilege
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