MegazoneCloud

Technology

Sr.AIFDE

$145–165k Rochester, New York, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Sr. AI FDE at MegazoneCloud. Skills: AI adoption, Agentic developer tooling, LLM-powered applications, Cloud AI services. Embed with customer teams. Translate business problems into AI architectures”

What You'll Achieve.

Drive adoption of AI; Deliver production AI systems; Achieve measured adoption; Own outcomes that stick; Meet performance targets; Meet security targets; Meet cost-efficiency targets; Ensure AI solutions are genuinely used; Meet adoption targets; Meet business impact targets; Meet ROI targets

Industry & Context.

Technology
Problems you'll solve

Troubleshoot complex issues

What They're Looking For.

Must Have

8–10+ years engineering production software, Hands-on experience building applications on AWS or Google Cloud, Demonstrated experience building with LLMs, Hands-on experience with agentic coding tools, Proficiency in Python, Proven client-facing communication skills, Experience mentoring engineers, Grasp of DevSecOps, SRE, and FinOps principles, Experience architecting data platforms, Integrate AI/ML services, Independently set up and configure cloud AI services

Nice to Have

Azure a plus, Experience leading technology-adoption programs, Experience leading developer-enablement programs, AWS Solutions Architect Professional certification, Google Professional Cloud Architect certification, Azure Solutions Architect Expert certification, AI/ML specialty certifications a plus

What You'll Do.

Embed with customer teams

Translate business problems into AI architectures

Own AI outcomes end to end

Design LLM-powered applications

Build LLM-powered applications

Deploy LLM-powered applications

Integrate with client data stores

Integrate with client APIs

Integrate with client security controls

Stand up AWS environments for AI

Stand up Google Cloud environments for AI

Enable Amazon Bedrock

Configure Amazon Bedrock

Enable Google Vertex AI

Configure Google Vertex AI

Configure model access

Configure service quotas

Drive enterprise adoption of agentic tooling

Secure rollout of agentic tooling

Manage identity isolation

Manage tenant isolation

Integrate agentic tooling with SDLC

Integrate agentic tooling with CI/CD

Enable developers with agentic tooling

Lead change management

Build golden-path templates

Build enablement assets

Define success metrics

Instrument success metrics

Rapidly prototype proofs-of-concept

Iterate prototypes into production systems

Establish reusable accelerators

Establish reference implementations

Establish AI delivery harnesses

Champion shift-left security

Champion responsible AI

Champion FinOps practices for AI

Mentor engineers during build

Troubleshoot complex issues

Serve as escalation point

Support pursuit teams

Present technical vision

Present adoption strategy

Publish internal knowledge articles

How You'll Work.

Team & Collaboration

Customer teams; Cloud engineers; Cross-functional teams

Communication Scope

Client-facing communication; Executive presentations; Technical vision; Adoption strategy

Full Job Description

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

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