Monks
ImplementationEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Implementation Engineer at Monks. Skills: AI systems, prompt engineering, AI agent configuration, API integrations, data workflows, cloud-based architectures, prototyping. Act as the primary liaison between Business Units, clients, and the Core Engineering team to ensure technical deliverables meet user needs. Collaborate with creative and operations teams to rework prompts, refine system instructions, and improve AI-driven experiences”
What You'll Achieve.
ensures that client needs are understood, validated, and efficiently translated into scalable technical solutions; rapidly prototypes, tests, and validates new AI-driven workflows and solutions; productionize and scale them across the broader system; empowering creative teams to harness AI tools effectively; refine prompts, optimize system instructions, and evolve new agents and features that push the boundaries of what’s possible
Industry & Context.
validate client needs; translate into scalable technical solutions; optimize system instructions; evolve new agents and features
Return to Office (RTO) policy
What They're Looking For.
Must Have
understanding of AI systems, particularly within the Google AI ecosystem (Vertex AI, Gemini, etc. ), Experience with prompt engineering, grounding, system instruction tuning, and AI agent configuration, Familiarity with API integrations, data workflows, and cloud-based architectures (especially Google Cloud), Proven ability to prototype quickly using tools such as Python, Apps Script, or no/low-code platforms, communication and stakeholder management skills, with experience working between technical and creative teams, Ability to document, train, and enable non-technical users effectively
Nice to Have
Background in applied AI, creative technology, or implementation engineering, Has worked with Google as a client before, Hands-on exposure to LLM orchestration frameworks and AI toolchains, Passion for experimentation and a “builder” mindset
What You'll Do.
Act as the primary liaison between Business Units
and the Core Engineering team to ensure technical deliverables meet user needs
Collaborate with creative and operations teams to rework prompts
refine system instructions
and improve AI-driven experiences
and maintain new AI agents and Agentic flows within existing tools and environments using existing Google frameworks
Collect and synthesize user and BU feedback into structured feature requests for the Core Engineering team
Maintain clear documentation on implementations
and workflows for cross-team transparency
Educate internal teams on new AI tools
and scalable implementation methods
How You'll Work.
Team & Collaboration
Act as the primary liaison between Business Units, clients, and the Core Engineering team; collaborate with Core Engineering to productionize and scale them; collaborate with creative and operations teams; working between technical and creative teams; cross-team transparency
Communication Scope
communication and stakeholder management skills; Ability to document, train, and enable non-technical users effectively
Full Job Description
Please note that we will never request payment or bank account information at any stage of the recruitment process. As we continue to grow our teams, we urge you to be cautious of fraudulent job postings or recruitment activities that misuse our company name and information. Please protect your personal information during any recruitment process. While Monks may contact potential candidates via LinkedIn, all applications must be submitted through our official website (monks.com/careers). About the Role The Implementation Engineer is a key bridge between the Business Unit (BU), the extended client organization, and the Core Engineering team. Acting as both advocate and enabler, this role ensures that client needs are understood, validated, and efficiently translated into scalable technical solutions. Deeply embedded in the Google AI ecosystem, the Implementation Engineer rapidly prototypes, tests, and validates new AI-driven workflows and solutions. Once proven, they collaborate with Core Engineering to productionize and scale them across the broader system. This role sits at the intersection of technology, creativity, and innovation—empowering creative teams to harness AI tools effectively, refine prompts, optimize system instructions, and evolve new agents and features that push the boundaries of what’s possible. Responsibilities: Client & BU Advocacy: Act as the primary liaison between Business Units, clients, and the Core Engineering team to ensure technical deliverables meet user needs. Workflow Optimization: Collaborate with creative and operations teams to rework prompts, refine system instructions, and improve AI-driven experiences. Agent/Agentic Development: Spin up, configure, and maintain new AI agents and Agentic flows within existing tools and environments using existing Google frameworks. Feature Translation: Collect and synthesize user and BU feedback into structured feature requests for the Core Engineering team. Technical Documentation: Maintain clea
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