Lead Forward Deployed Engineer – AI & Operations - Pipeline

Forvis Mazars in South Africa; Johannesburg; On-site; ZAR 800,000 - 1,200,000; Full time

Job summary

Forvis Mazars in South Africa is seeking a Lead Forward Deployed Engineer – AI & Operations to work in a client-facing role that bridges industrial engineering and operational transformation. This position involves identifying operational issues and designing solutions with measurable impacts.

The ideal candidate will have over 5 years of experience and a background in industrial engineering or equivalent fields. Responsibilities include embedding with client teams, mapping processes, and leading the adoption of new workflows and solutions.

Qualifications

• 5+ years of relevant experience.
• Proficiency in data and technology.
• Ability to navigate complex operational sectors.

Responsibilities

• Embed with client teams to understand their operations.
• Translate business problems into prioritized opportunities.
• Design future-state workflows.
• Facilitate working sessions with various stakeholders.
• Lead solution adoption and manage resistance.

Skills

Experience in industrial engineering

Digital transformation

Technical consulting

Data analysis

AI prototyping

SQL

Python

Emotional intelligence

Systems thinking

Education

Industrial Engineering or equivalent

Computer Science

Job description

Forvis Mazars is hiring a Lead Forward Deployed Engineer – AI & Operations for a client-facing role that sits between industrial engineering, client advisory, data/AI delivery, and operational transformation.

This role is for someone who can walk into a client environment where the problem is not yet clear, earn trust with executives and frontline teams, find the operational issue worth solving, and help turn it into a working solution that people actually use.

Your why?

You will work across people, process, data, AI, automation, and technology. The job is about moving from problem discovery to solution design, prototype, deployment, adoption, and measurable impact.

The right candidate is curious, commercially aware, comfortable with ambiguity, and willing to spend time where the work happens. We care less about perfect role titles and more about evidence that you have improved a real operating environment and brought people with you.

What You Will Do

• Embed with client teams to understand operations, decisions, workflows, pain points, data, and constraints
• Translate ambiguous business problems into clear, prioritised opportunities
• Map current-state processes and identify root causes, bottlenecks, risks, and value leakage
• Design practical future-state workflows using the right mix of people, process, data, AI, automation, and controls
• Build or lead rapid prototypes and work with technical specialists to move solutions toward production
• Define success measures, baselines, adoption plans, and benefits cases
• Facilitate working sessions with executives, operational leaders, technical teams, and users
• Lead adoption, manage resistance, and help clients change how work actually gets done
• Turn successful delivery patterns into reusable offerings, playbooks, demos, and accelerators
• Support client pitches, solution shaping, and follow-on opportunity development

What We Are Looking For

• 5+ years of experience in industrial engineering, digital transformation, technical consulting, implementation, product, data, AI, automation, or a related field
• Evidence of taking ambiguous operational problems through to implemented, measurable outcomes
• Strong systems thinking across people, process, incentives, data, technology, risk, and governance
• High emotional intelligence and confidence working from the frontline to the C-suite
• Practical fluency with data and technology, including SQL and ideally Python, APIs, analytics, automation, or AI prototyping
• Ability to explain complex ideas clearly and make pragmatic trade-offs across value, effort, speed, risk, and adoption
• A low-ego, high-agency working style and willingness to spend time where the work happens
• Industrial Engineering, Systems Engineering, Operations Research, Computer Science, Information Systems, or equivalent practical experience
• Experience delivering AI, data, automation, enterprise workflow, digital twin, or knowledge graph solutions
• Experience in consulting, enterprise technology, product implementation, or an entrepreneurial environment
• Exposure to complex operational sectors such as financial services, mining, manufacturing, logistics, energy, retail, healthcare, or the public sector