Sr. AI FDE

Job Description

At MegazoneCloud, we help the world’s most innovative companies adopt AI that actually delivers — not pilots that stall, but production systems that get used. As an AI Forward Deployed Engineer (FDE), you embed directly with global clients to drive the adoption of leading AI platforms and agentic developer tooling: generative and agentic AI solutions on AWS and Google Cloud, and agentic coding tools from Anthropic (Claude Code), OpenAI (Codex), and AWS (Kiro).

You sit at the intersection of engineering and customer success — rapidly prototyping, integrating with client environments, and owning solutions from proof-of-concept through production and into real, measured adoption. This is an ownership role: you are accountable for outcomes that stick, not just deliverables that ship. You’ll apply best-practice automation — infrastructure as code (IaC), CI/CD, and DevSecOps — to deliver AI workloads that meet demanding performance, security, and cost-efficiency targets.

Key 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

• 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.

Why You'll Love It Here

• Our Product is Our People: We live by this. We invest in people who invest in themselves. Your growth is our growth.
• True Servant Leadership: Our CTO leads with a "force multiplier" philosophy. Management is here to empower you and clear roadblocks, not to micromanage. We won't ask you to do anything we're not willing to do ourselves.
• Flat Organization, Real Impact: Your voice and designs will directly shape our technical roadmap and our clients' success. You'll work on the latest tech to solve real problems.
• A "Learn-from-it" Culture: We're moving fast and building new things. We believe mistakes are learning opportunities, not failures.

We seek diverse talent who are ready to make an immediate impact. We believe that innovation thrives when teams are built with a variety of backgrounds, experiences, and perspectives. If you are excited by this mission, we encourage you to apply, even if your experience doesn't perfectly match every qualification listed.

Megazone Cloud is an Equal Opportunity Employer and participates in E-Verify to confirm the employment eligibility of all new hires.

Compensation Range: $145K - $165K