Descrizione dell'offerta
Experteer Overview
As a Forward Deployed AI Engineer, you embed with client teams to turn AI platform capabilities into measurable business value in real enterprise environments. You own outcomes such as time-to-value, adoption, reliability, and scalability across multiple workstreams, not just delivery milestones. You work on enterprise-scale AI deployments, shaping strategy and reusable patterns for the FDE practice. This role puts you at the interface of technology and business leadership, tackling hard AI adoption challenges and delivering production-ready solutions. You join a growing deployment engineering cohort that tackles high-impact, cross-industry AI problems. Retribuzione / Benefits
Lead enterprise AI platform deployments across complex client environments and partner ecosystems, owning architecture through adoption Own programme-level delivery outcomes including time-to-value, reliability, adoption velocity, and scalability with commercial metrics Drive rapid experimentation to transform ambiguous business problems into production systems within days or weeks Architect and govern enterprise AI solutions across identity, data, security, governance, and multi-system integration at programme scale Shape reinvention strategy for client leadership with value architectures, ROI backlogs, and multi-year adoption roadmaps Define and publish reusable blueprints, patterns, and accelerators for scaling across client engagements Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite teams Codify delivery learnings and engineering standards to evolve the FDE practice Responsabilità
Extensive engineering experience with cloud-native systems (APIs, microservices, containerization, serverless) Deep expertise in agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production Experience with AI platforms - OpenAI, Claude, Vertex AI, and open-source models and building abstraction layers for multi-provider pipelines Experience leading software engineering teams and owning delivery across workstreams Proven end-to-end delivery ownership in client-embedded environments Ability to quantify business value deployments in CFO-recognizable terms Experience presenting to senior client stakeholders (CTO, CFO, CISO) Non-linear profiles welcomed; emphasis on deployment outcomes over CV patterns People leadership: managing and developing a team of engineers and conducting career conversations
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As a Forward Deployed AI Engineer, you embed with client teams to turn AI platform capabilities into measurable business value in real enterprise environments. You own outcomes such as time-to-value, adoption, reliability, and scalability across multiple workstreams, not just delivery milestones. You work on enterprise-scale AI deployments, shaping strategy and reusable patterns for the FDE practice. This role puts you at the interface of technology and business leadership, tackling hard AI adoption challenges and delivering production-ready solutions. You join a growing deployment engineering cohort that tackles high-impact, cross-industry AI problems. Retribuzione / Benefits
Lead enterprise AI platform deployments across complex client environments and partner ecosystems, owning architecture through adoption Own programme-level delivery outcomes including time-to-value, reliability, adoption velocity, and scalability with commercial metrics Drive rapid experimentation to transform ambiguous business problems into production systems within days or weeks Architect and govern enterprise AI solutions across identity, data, security, governance, and multi-system integration at programme scale Shape reinvention strategy for client leadership with value architectures, ROI backlogs, and multi-year adoption roadmaps Define and publish reusable blueprints, patterns, and accelerators for scaling across client engagements Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite teams Codify delivery learnings and engineering standards to evolve the FDE practice Responsabilità
Extensive engineering experience with cloud-native systems (APIs, microservices, containerization, serverless) Deep expertise in agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production Experience with AI platforms - OpenAI, Claude, Vertex AI, and open-source models and building abstraction layers for multi-provider pipelines Experience leading software engineering teams and owning delivery across workstreams Proven end-to-end delivery ownership in client-embedded environments Ability to quantify business value deployments in CFO-recognizable terms Experience presenting to senior client stakeholders (CTO, CFO, CISO) Non-linear profiles welcomed; emphasis on deployment outcomes over CV patterns People leadership: managing and developing a team of engineers and conducting career conversations
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Candidatura e Ritorno (in fondo)
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