Forward Deployed Engineer, Torque

Summarised Purpose Of The Job
Torque is Syspro's Industrial AI platform, live at select pilot sites and built to put AI to work inside real manufacturing and distribution operations. This is the first dedicated Forward Deployed Engineer role.
The Forward Deployed Engineer embeds with customers to find where AI creates genuine operational value (value discovery) and makes Torque deliver it fast (time-to-value), owning each engagement from technical discovery through production rollout and customer enablement. Torque sells alongside Syspro ERP and standalone to companies running other ERPs, so every strong deployment opens the door to new customers.
The role sits in a small founding team and reports to the Chief Operating Officer. It is based in Johannesburg, with engagements run mostly remotely and on site when required or preferred. It suits an engineer who wants to build with frontier AI on real industrial problems, ship to production in weeks, and shape the success of a next-generation product and function from day one.

Responsibilities

Key Responsibilities
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Value discovery and product-market fit

• Identify with pilot customers the operational problems where Torque creates the most value, and pressure-test the value proposition against reality
• Trial use cases fast: prototype, deploy, measure, keep what works and cut what does not
• Quantify outcomes in the customer's own data and feed the evidence to the Torque product, Presales and Product Marketing teams

Deployment, enablement and time-to-value

• Own deployment end to end at assigned accounts, from technical discovery through production rollout
• Define a first-value milestone with each customer (a measurable operational outcome, not a go-live date) and drive the engagement to reach it quickly
• Connect, configure and extend Torque against the customer's ERP and operational data, whether they run Syspro or another system
• Enable customer teams to run Torque themselves, and make the value visible to their leadership in their own numbers

Forward-deployed customer engagement

• Engaged customers primarily remotely, going deep on their data, systems and operational realities

• Build trust from the shop floor to the executive sponsor, adapting solutions to how they perform in practice
• Support Presales with technical depth in demos and proof-of-value engagements

Building the playbook

• Turn engagements into reusable assets: integration patterns, agent configurations, data mappings and deployment playbooks
• Cut deployment time with every successive engagement, so Torque scales beyond what one engineer can deliver in person
• Set the tooling, methods and standards the Forward Deployed Engineering function grows on

Governance, quality and responsible AI

• Ensure deployed solutions meet Syspro standards for accuracy, security and reliability
• Handle customer and company data in line with Syspro data-protection and IT governance policy (POPIA, GDPR, ISO 27001)
• Document deployments for supportability after handover, applying responsible-AI practice (testing, human oversight) throughout

Requirements

Minimum education

• Bachelor's degree in Computer Science, Software Engineering, Data Science or a related field; or equivalent practical experience

Beneficial qualifications

• Certification in AI/ML, data engineering or a cloud platform (e.g., Azure, AWS or Google Cloud)
• ERP product certification (Syspro or comparable)

Minimum experience

• Building and shipping software in production
• Building with LLMs and/or agents, APIs and data pipelines
• Deploying solutions with customers or end users in live operational environments, including integrating data across business systems

Beneficial experience

• Syspro or another ERP: data model, integration patterns and implementation lifecycle
• A forward-deployed, professional services, presales or solutions-engineering role
• Manufacturing or distribution environments, or an early-stage, zero-to-one product build

Special skills and knowledge

• Practical command of modern AI tooling: LLMs, agent frameworks, prompt design and APIs
• Reads a customer's data landscape and operational context quickly and designs solutions that fit it
• Translates operational problems into technical solutions and explains them to any audience
• Bias for building: prototypes fast, iterates on feedback and ships working tools in live environments
• Comfortable with ambiguity and ownership; energised rather than unsettled by a role without a template
• Handles customer data with care: confidentiality, security and responsible use throughout