{"id":1731,"date":"2026-06-29T00:31:13","date_gmt":"2026-06-29T00:31:13","guid":{"rendered":"https:\/\/coderseditor.com\/itjobs\/job\/forward-deployed-engineer-google-cloud-consulting-4\/"},"modified":"2026-06-29T00:31:13","modified_gmt":"2026-06-29T00:31:13","slug":"forward-deployed-engineer-google-cloud-consulting-4","status":"publish","type":"job_listing","link":"https:\/\/coderseditor.com\/itjobs\/job\/forward-deployed-engineer-google-cloud-consulting-4\/","title":{"rendered":"Forward Deployed Engineer, Google Cloud Consulting"},"content":{"rendered":"

Forward Deployed Engineer, Google Cloud Consulting Overview<\/h2>\n\n\n\n\n\n\n\n\n
Company Name<\/strong><\/td>\nGoogle<\/td>\n<\/tr>\n
Job Role<\/strong><\/td>\nForward Deployed Engineer, Google Cloud Consulting<\/td>\n<\/tr>\n
Qualifications<\/strong><\/td>\nBachelor’s<\/td>\n<\/tr>\n
Category<\/strong><\/td>\nIT Jobs<\/td>\n<\/tr>\n
Job Type<\/strong><\/td>\nFull Time<\/td>\n<\/tr>\n
Location<\/strong><\/td>\nLondon<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

This role sits within Google Cloud Consulting and is focused on embedding directly with customers to turn advanced AI concepts into working systems in real production environments. Rather than operating as a traditional advisor, the engineer is expected to be a hands-on builder who codes, debugs, and helps deliver bespoke agentic solutions alongside the customer. The position is aimed at highly self-directed engineers who can move quickly, think like founders, and remove the practical obstacles that often stop AI projects from reaching enterprise scale.<\/p>\n

The work centers on helping customers bridge the gap between frontier AI capabilities and the realities of live business systems. That includes solving integration challenges, improving data readiness, handling state-management issues, and making sure solutions are robust enough for enterprise use. The role also has a feedback loop into Google Cloud itself, since insights gathered in the field are expected to inform future product direction and improvements.<\/p>\n

What you will do<\/h3>\n
    \n
  • Build and ship complex AI applications, taking them from early prototypes into production-ready agentic workflows that can include multi-agent systems and MCP servers, with a clear focus on business value and measurable return on investment.<\/li>\n
  • Develop the technical connections between Google\u00e2\u0080\u0099s AI products and the customer\u00e2\u0080\u0099s live systems, including APIs, older data repositories, and security controls, while collaborating with a specialist team.<\/li>\n
  • Create strong evaluation, monitoring, and observability frameworks so that agentic systems can be assessed for accuracy, safety, and latency.<\/li>\n
  • Run technical discovery sessions with customers to understand their goals, constraints, and implementation challenges.<\/li>\n
  • Identify recurring issues and patterns seen in customer deployments, then translate those findings into reusable building blocks or formal product requests for Google\u00e2\u0080\u0099s engineering teams.<\/li>\n
  • Partner with pre-sales and product teams to promote Google\u00e2\u0080\u0099s engineering practices and help ensure solutions are adopted successfully and continue to deliver value over time.<\/li>\n
  • Help customers overcome the main blockers to enterprise AI adoption, including integration complexity, incomplete data readiness, and state-management problems.<\/li>\n
  • Act as a deployment-focused engineer who works inside customer environments and helps convert field experience into product and platform improvements.<\/li>\n<\/ul>\n

    What the role requires<\/h3>\n
      \n
    • A bachelor\u00e2\u0080\u0099s degree in engineering, computer science, a related subject, or equivalent hands-on experience.<\/li>\n
    • At least five years of software development experience using Python or a similar language.<\/li>\n
    • Experience bringing AI-driven solutions from concept to launch in production settings.<\/li>\n
    • Experience designing AI systems on cloud platforms such as Google Cloud Platform.<\/li>\n
    • Experience creating pipelines for both structured and unstructured data, using vector databases and retrieval-augmented generation-style architectures to support enterprise AI use cases.<\/li>\n
    • Experience leading technical discovery conversations with customers.<\/li>\n
    • Preferred: a master\u00e2\u0080\u0099s degree or PhD in AI, computer science, or another related technical area.<\/li>\n
    • Preferred: experience building multi-agent systems using tools such as LangGraph, CrewAI, or ADK, along with advanced design patterns such as ReAct, self-reflection, and hierarchical delegation.<\/li>\n
    • Preferred: experience in post-sales delivery or technical consulting.<\/li>\n
    • Preferred: knowledge of LLM-oriented operational metrics such as tokens per second and cost per request, as well as techniques for state management and detailed tracing.<\/li>\n
    • This is a mid-level position, so the successful candidate should be comfortable driving progress, solving difficult problems, and mentoring less experienced team members.<\/li>\n
    • Because Google operates globally, English proficiency is required unless a posting explicitly states otherwise.<\/li>\n<\/ul>\n

      Team and environment<\/h3>\n

      You will be part of Google Cloud\u00e2\u0080\u0099s go-to-market organization, working at the intersection of customer delivery, product feedback, and advanced AI engineering. The environment is described as collaborative and highly technical, with direct access to Google\u00e2\u0080\u0099s broader AI capabilities, including Gemini models and the Vertex AI platform. The role also offers exposure to DeepMind engineering and research expertise, which is intended to help you solve difficult customer problems and deliver sophisticated solutions.<\/p>\n

      The company emphasizes a culture of belonging and equal opportunity. Applicants who need workplace accommodations can request support through the applicant accommodations process. Google also notes that it does not accept agency resumes and will not pay fees for unsolicited submissions.<\/p>\n

      Additional information<\/h3>\n

      Google states that information collected through a Careers profile and any submitted application is handled under its Applicant and Candidate Privacy Policy. The company also reiterates its equal opportunity and affirmative action commitments, including non-discrimination protections across a wide range of legally protected characteristics.<\/p>\n

      Equity, where granted, is handled solely at Alphabet\u00e2\u0080\u0099s discretion and is governed by the relevant stock plan, board or delegate approval, and the grant agreement. The posting also explains that such grants are not guaranteed and do not affect statutory payments.<\/p>\n

      The role is based in London, UK and is presented as a customer-embedded, hands-on engineering position rather than a remote-only advisory role.<\/p>\n\n

      Degree Requirement:<\/strong> Bachelor’s<\/p>\n

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