AI Forward Deployed Engineer

As a Forward Deployed AI Engineer, you will operate inside client environments to transform AI platform capabilities into measurable business value. You own outcomes such as time-to-value, adoption, reliability, and scalability across complex, multi-stakeholder settings. You work closely with executive stakeholders to shape strategy and ensure production-grade deployments that scale beyond pilots. This role combines hands-on engineering with strategic alignment to client goals, at scale.

• Lead enterprise AI platform deployments across multi-stakeholder client environments and own the full programme from architecture to adoption
• Manage programme-level delivery outcomes including time-to-value, reliability, adoption velocity, and scalability with commercial metrics
• Lead rapid experimentation to deliver working production systems within days or weeks in complex enterprises
• Architect and govern AI solutions across the full tech stack: identity, data, security, governance, platform layer, and cross-system integration
• Shape AI reinvention strategy for client executives: build value architectures, ROI backlogs, prioritization frameworks, and multi-year adoption roadmaps
• Define and publish reusable reinvention blueprints, patterns, and accelerators that scale across engagements
• Lead architecture design sessions, executive workshops, and code-with sessions with client teams and leadership
• Codify delivery learnings and engineering standards to evolve the FDE practice and enable future engineers
• Gain experience with cloud-native systems (APIs, microservices, containerization, serverless) and agentic AI solutions (agents, orchestration, RAG, workflows)
• Work with AI platforms (OpenAI, Claude, Vertex AI, Open-source models) including building abstraction layers for multi-provider pipelines
• Lead software engineering teams: delivery oversight, resource allocation, and developing direct reports
• Demonstrate end-to-end delivery ownership in client-embedded environments; not just internal projects or vendor labs
• Articulate business value in terms a CFO would recognize and act on
• Present to and build trust with senior client stakeholders (CTO, CFO, CISO)

• Proven end-to-end delivery ownership in client-embedded environments
• Experience leading software engineering teams and managing multiple workstreams
• Ability to quantify business value and communicate with senior stakeholders
• Strong background in enterprise AI deployments and platform integration
• Familiarity with cloud-native architectures and multi-provider AI platforms
• Proven ability to translate platform capabilities into measurable outcomes

• strong stakeholder management
• executive communication
• leadership and people development
• cloud-native systems (APIs, microservices, containerization, serverless)
• agentic AI solutions (agents, orchestration, context engineering, RAG, workflows)
• AI platforms (OpenAI, Claude, Vertex AI, open-source models)