Lead the engineering team responsible for delivering Redwood's shared AI platform and agentic capabilities, translating AI strategy into an executable engineering roadmap.
Responsibilities
Lead one or more engineering teams responsible for AI platform services, agentic capabilities, developer tools, and product integrations
Translate business and product priorities into a clear engineering roadmap, delivery plan, and team-level objectives
Recruit, onboard, manage, and retain engineers with the skills required to build production-grade AI and agentic systems
Establish clear ownership, performance expectations, decision-making responsibilities, and development plans across the team
Drive predictable execution through effective planning, dependency management, risk identification, and operational readiness
A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability.
Responsibilities
Lead enterprise AI platform deployments across complex multi-stakeholder client environments
Own programme-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple concurrent workstreams, with commercial metrics attached
Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments
Architect and govern enterprise AI solutions across the full technology stack: identity, data, security, governance, platform layer, and multi-system workflow integration at programme scale
Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use case prioritisation frameworks, and multi-year AI adoption roadmaps
A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. The role owns outcomes: time-to-value, adoption, reliability, and scalability.
Responsibilities
Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — inside enterprise environments
Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability, with business metrics attached
Move from ambiguous business problem to working production system through rapid experimentation: days to prototype, weeks to production-ready
Design and govern AI architectures across the full enterprise stack: identity, data, security, governance, platform layer, and workflow integration
Translate technical architecture into business impact for client CTO, CFO, and CISO; shape use case roadmaps, ROI backlogs, and AI adoption strategy
A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability.
Responsibilities
Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — inside enterprise environments
Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability, with business metrics attached
Move from ambiguous business problem to working production system through rapid experimentation: days to prototype, weeks to production-ready
Design and govern AI architectures across the full enterprise stack: identity, data, security, governance, platform layer, and workflow integration
Translate technical architecture into business impact for client CTO, CFO, and CISO; shape use case roadmaps, ROI backlogs, and AI adoption strategy
A hands-on technical leadership role focused on building software, validating emerging technologies, creating production-grade prototypes, and influencing future product and technology direction across IFS, specializing in applied AI and agentic systems.
Responsibilities
Identify, evaluate, and validate emerging technologies, architectural patterns, and industry trends relevant to IFS products and customers.
Design, build, and deliver prototypes, proof-of-concepts, and production-ready capabilities across software engineering, cloud, data, and AI domains.
Lead technical investigations and architectural studies, producing clear recommendations, reference implementations, and actionable next steps.
Drive complex technical initiatives from concept through implementation and product handover, applying agentic engineering and AI-assisted workflows to accelerate delivery.
Collaborate closely with Product Management, Industry teams, Engineering teams, Sales, Presales, customers, and partners to validate ideas, solve real business problems, and shape future IFS products and technology direction.
Requirements
Bachelor's degree in Software Engineering, Computer Science, Information Technology, or a related field
Lead the technical strategy and architectural direction for Group AI Enablement, connecting enterprise AI ambitions with the engineering foundations needed to deliver them.
Locations (2)
Sydney, New South Wales, Australia
Melbourne, Victoria, Australia
Responsibilities
Define the long-term engineering strategy and architecture for enterprise AI capabilities.
Shape how AI models, agents, knowledge sources and business systems integrate, establishing patterns that enable security, interoperability and reuse.
Lead complex engineering initiatives from discovery and experimentation through to production.
Build reusable services, reference implementations and engineering patterns covering identity, permissions, observability and operational ownership.
Establish rigorous approaches to evaluating RAG and agentic systems using representative business tasks and measurable success criteria.
Senior Software EngineerAxon · Seattle, US
Senior Manager, AI CoERedwood Software · Hyderabad, India
Head of Engineering, CardsCareers at Tide · United Kingdom+1 more