Forward Deployed Engineer
New
H
Hire OverseasData and AI consulting
Workable locations: Argentina. El Salvador. Peru. Colombia. Brazil. Mexico, Availability during US business hoursFull-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- Professional English proficiency at C1 or C2 level minimum
- Experience
- 3 to 5 years of software or data engineering experience
- Required Skills
- PythonJavascriptTypeScriptReact
Requirements
- Have 3 to 5 years of software or data engineering experience and extensive hands-on use of AI tools and LLM-based development over the past year.
- Have strong programming skills in Python and TypeScript or JavaScript, including experience building and consuming APIs.
- Have front-end development experience with React or similar frameworks and at least one backend framework.
- Have hands-on experience with RAG, embeddings, and vector search.
- Have experience with at least one agentic framework: LangGraph, LangChain, Google ADK, Claude Agent SDK, or OpenAI Agents SDK.
- Have deep specialization in at least one major AI platform ecosystem: Google, Anthropic, or OpenAI.
- Have working experience with at least one cloud platform—GCP, Azure, or AWS—and experience building and maintaining data pipelines.
- Be fluent with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor.
- Have professional English proficiency at C1 or C2 level minimum and availability during US business hours.
- Have a bachelor's or master's degree in computer science, engineering, or a related field, or equivalent practical experience.
- Hold a certification on at least one major AI platform or cloud, or obtain one within the first two months.
Responsibilities
- Develop user-facing interfaces in TypeScript and React, with backend services and APIs in Python or Node.
- Implement agentic behavior, including orchestration, tool and function calling, memory, and guardrails.
- Build RAG pipelines for ingestion, chunking, embeddings, and vector and hybrid search.
- Connect AI systems to enterprise data and applications through APIs, semantic layers, and protocols such as MCP.
- Write evaluation suites and regression tests for LLM-powered features, and monitor production cost, latency, and quality.
- Apply version control, code review, automated testing, CI/CD, and observability practices.
- Deploy on GCP, Azure, or AWS and build and maintain data pipelines feeding AI systems.
- Communicate progress, trade-offs, and blockers to clients and project leads, and support pre-sales scoping, demos, and effort estimates.
- Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards.
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