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Job Summary:
MegazoneCloud Global helps innovative companies adopt AI that delivers real results. As a Senior AI Forward Deployed Engineer, you will work directly with global clients to implement AI solutions, ensuring successful integration and adoption of advanced AI platforms and tools.
Responsibilities:
• Embed with customer teams to translate business problems into production AI architectures spanning models, data, application, and operations — owning the outcome end to end.
• Design, build, and deploy LLM-powered applications — including RAG pipelines, agentic workflows, and orchestration frameworks — integrated with client data stores, APIs, and security controls.
• Stand up the AWS and Google Cloud environments needed for AI services — enabling and configuring Amazon Bedrock, SageMaker, Google Vertex AI, and related resources (IAM roles, networking, model access, and service quotas) self-sufficiently within client guardrails, partnering with dedicated cloud engineers for deeper foundational account and landing-zone setup.
• Drive enterprise adoption of agentic developer tooling (Anthropic Claude Code, OpenAI Codex, AWS Kiro): secure rollout, identity and tenant isolation, SDLC and CI/CD integration, and the developer enablement that turns licenses into measurable productivity.
• Lead adoption and change management — build golden-path templates, enablement assets, and team workflows so AI solutions and tools are genuinely used, not merely delivered.
• Define and instrument success — adoption, business impact, and ROI metrics — and iterate post-launch until targets are met.
• Rapidly prototype proofs-of-concept and iterate them into production-grade systems alongside the customer.
• Establish reusable accelerators, reference implementations, and AI delivery harnesses applicable across engagements.
• Champion shift-left security, responsible AI, and FinOps practices for AI workloads, including token-cost and model-routing discipline.
• Mentor engineers during build and deployment; troubleshoot complex issues spanning models, infrastructure, application, and data layers.
• Serve as an escalation point during go-live and hyper-care.
• Support pursuit teams with solution diagrams, scoping, and engagement estimation.
• Present technical vision and adoption strategy to C-suite and enterprise architects.
• Publish blog posts, white papers, and internal knowledge articles.
Qualifications:
Required:
• 8–10+ years engineering production software, with hands-on experience building applications on at least one major cloud platform — AWS or Google Cloud preferred (Azure a plus).
• Demonstrated experience building with LLMs (e.g., Anthropic Claude, OpenAI, Gemini) — prompt engineering, RAG, and agentic systems.
• Hands-on experience with agentic coding tools (e.g., Claude Code, Codex, Kiro), and a practical understanding of how to roll them out and drive adoption across an engineering organization.
• Proficiency in Python and at least one additional language (e.g., TypeScript/JavaScript, Java, Go).
• Proven client-facing communication skills — able to defend architectural and model decisions with executives and engineers alike, and to drive adoption through influence.
• Experience mentoring engineers.
• Strong grasp of DevSecOps, SRE, and FinOps principles.
• Experience architecting data platforms and integrating AI/ML services.
• Able to independently set up and configure cloud AI services and their supporting resources (e.g., Amazon Bedrock, SageMaker, Google Vertex AI; IAM, networking, model access, and quotas) on AWS and/or Google Cloud — self-sufficient for the services the role needs, with foundational account and landing-zone build-out handled in partnership with dedicated cloud engineers.
• Exposure to serverless patterns, event-driven architectures, MCP integration, and vector databases.
• Experience leading technology-adoption or developer-enablement programs is a strong plus.
• Bachelor’s degree in Computer Science or similar.
• Certifications: AWS Solutions Architect Professional, Google Professional Cloud Architect, or Azure Solutions Architect Expert (one required, multiples preferred); AI/ML specialty certifications a plus.
Company:
MegazoneCloud stands as Asia's leading cloud managed service provider (MSP) and digital transformation catalyst, revolutionizing how enterprises harness cloud technology. Founded in 1998, the company is headquartered in Gwacheon-si, Gyeonggi-do, KR, , with a team of 1001-5000 employees. The company is currently Late Stage.