GenAI Engineer

Costa Rica·Escazumid

OtherGenai Engineer

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Key Responsibilities

Design and develop GenAI solutions using prompt engineering, Retrieval-Augmented Generation (RAG),

Technical Tools

OtherGenai Engineer

Over 10 years of robust software engineering experience, including 2 to 3 years of dedicated hands-on work in Generative AI and Retrieval-Augmented Generation (RAG) architecture
Over 3 years of cloud native experience preferably on AWS.
Over 5 years of hands-on experience with Python
Experience building interoperable Agentic AI Proof of Concepts using Model Context Protocol (MCP) and/or Google A2A.

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→Design and develop GenAI solutions using prompt engineering, Retrieval-Augmented Generation (RAG), and custom pipelines
→Design and develop interoperable AI agents using Model Context Protocol (MCP) and Google A2A
→Automate workflows involving parsing unstructured content such as emails, documents, and web pages in to highly accurate and reliable structured content
→Automate building documents using data and content from various diverse sources
→Build enterprise-wide reusable services and components
→Design and build MCP hosts, clients and servers
→Establish frameworks for automated LLM testing
→Create regression test suites to detect drift or prompt breakage
→Integrate with internal and external web services using secure authentication and authorization mechanisms
→Adopt and ensure safe practices to protect against prompt injections, jailbreaks, and conform to enterprise security guidelines
→Experience with agile methodologies and ability to independently document user stories in the absence of Business Analyst
→Collaborate with the AI CoE team to ensure scalability, reusability, and alignment with governance standards

Very strong Python skills.
Strong hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Gemini, Anthropic, etc.) using Python and Python based frameworks
Strong hands-on experience in prompt engineering, context construction, grounding strategies
Strong hands-on experience with Retrieval Augmented Generation (RAG) extracting, chunking and create embeddings from unstructured documents from diverse sources including O365(email, word, excel), PDFs, and webpages.
Comfortable building Model Context Protocol (MCP) clients, servers and hosts.
Strong Expertise in building REST APIs and integrating with internal/external APIs
Hands-on experience with Intelligent Document Processing and/or OCR technologies on complex documents
Knowledge of Google A2A
Deep experience in AWS (Lambda, Bedrock, Step Functions, API Gateway, IAM)
Strong experience with monitoring using LangSmith, CloudWatch, or other similar GenAI observability tools
Excellent GenAI foundations and concepts
Clear understanding of enterprise data privacy, AI governance, and observability

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Experience with Microsoft Copilot extensibility (Graph connectors, plugins, or adaptive cards)
Ability to build and orchestrate AI-to-AI interactions using Google A2A, integrating multiple agents or tools
Strong traditional ML Experience

You’re a builder who can translate fuzzy business needs into elegant GenAI and Agentic AI workflows
You’re a problem solver who’s comfortable navigating across cloud platforms, tools, and data sources
You’re collaborative, with the ability to work independently while aligning with enterprise AI goals