Hi Katie,

I am applying for the Solutions Engineer, Enterprise role.

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I close the technical win — then I help ship the first milestone.

Eliecer Vera. 9+ years full-stack. GenAI practitioner. GTM-embedded with AE, AM, and CSM teams at Swoogo.

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Years shipping software
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POCs delivered to clients
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AI tools used daily
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SaaS companies
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Why Scale AI

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Meta. DoD. The frontier of AI.

Scale’s customers are not just enterprises — they are institutions.

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Meta. DoD. The frontier of AI.

Scale’s customer list reads like the who’s-who of AI: Meta, the U.S. Army, the Air Force, Cisco, Mayo Clinic. These are not early adopters — they are deploying AI at institutional scale. Being the SE on those technical wins, designing GenAI solutions for customers whose decisions affect millions of people — that is the kind of work I want to be doing. The Meta partnership alone signals that Scale is not adjacent to frontier AI. Scale is foundational to it.

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AI data quality is the moat. You own it.

The foundation of every great model runs through Scale.

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AI data quality is the moat. You own it.

Every frontier model being trained today needs high-quality data and rigorous evaluation. Scale sits at the center of that. As an SE, I would be selling and scoping solutions that are literally foundational to how AI develops — not selling dashboards or integrations, but the infrastructure that powers the world’s best models. I understand GenAI deeply enough to have real credibility with the ML engineers I am selling to. That is the edge I bring.

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Built for the SE role at Scale.

Here is how my experience maps directly to what you are looking for.

GTM Partnership & Technical Win

I have done the SE job — partnering with AEs to close deals — without the SE title.

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GenAI Fluency for Enterprise Customers

Not talking-point knowledge — I use GenAI in production every single day.

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What I bring

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Customer-Facing Technical

I have delivered POCs, scoped requirements, and explained complex systems to non-technical stakeholders — all while maintaining technical credibility with the engineering teams on the other side of the table. Both at the same time.

GenAI Depth

LLMs, RAG pipelines, AI agents, prompt engineering — this is how I build every day. When a customer asks about fine-tuning vs. RAG, agent orchestration costs, or evaluation methodology, I can go deep. Not slides. Actual architecture.

GTM-Embedded

Worked with AEs, AMs, and CSMs at Swoogo to help close enterprise deals. I understand pipeline language, know how to prep for discovery calls, and know what ‘remove the technical blocker’ actually means when a deal is on the line.

Full-Stack Builder

9+ years of production code: PHP/Laravel, React/TypeScript, Node.js, AWS, Python. I can build POCs fast, review customer integration code confidently, and scope post-sales implementation with the precision of someone who has to build it.

GenAI is Scale’s domain — I work in it every day

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Scale AI’s product is AI infrastructure: data labeling, RLHF, model evaluation, enterprise AI deployment. Every SE conversation at Scale is a deep technical conversation about GenAI. That is not a gap I need to fill — it is the space I already operate in.

02

I use Claude Code every day to ship production software. I have integrated OpenAI APIs, built RAG pipelines, designed multi-step AI agents, and evaluated model outputs for quality. I understand the tradeoffs between RAG and fine-tuning, the cost structure of LLM inference, and what enterprise customers worry about when deploying AI at scale — latency, cost, data privacy, evaluation methodology.

03

Python is my weakest listed language, but I am semi-fluent — enough to build GenAI prototypes, evaluate LangChain or LlamaIndex pipelines, and work productively with ML engineers on implementation. I learn fast and I have been learning this space while building in it, not studying it from the outside.

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The real SE edge at Scale is being able to walk into a Fortune 500 engineering team and have a credible technical conversation about AI architecture — not selling features, but designing solutions. Technical depth, customer fluency, and GTM alignment in the same person. That is what I offer.

Claude CodeOpenAI APIsRAG PipelinesAI AgentsLangChainLlamaIndexPrompt EngineeringPython

Let’s talk.

I would love to discuss how my background in full-stack engineering, GenAI tooling, and GTM collaboration maps to what Scale needs in this SE role. I am the technical voice that closes the technical win — and stays to help deliver the first implementation milestone.

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P.S. Based in Orlando, FL. Open to travel to San Francisco or New York. Available to start in 2 weeks.