Senior Forward Deployed Engineer, AI Platform

🔥 10 hours ago

🌐 Colombia, Costa Rica – Remote

🇨🇴 Colombia – Remote 🇨🇷 Costa Rica – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Gorilla Logic

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Gorilla Logic is a company renowned for its expertise in modern software and data engineering. Serving as a strategic partner rather than just a vendor, Gorilla Logic specializes in digital product design, cloud engineering, data and AI delivery, DevOps, quality assurance, and legacy modernization. With a team of skilled digital product designers, solutions architects, and Agile nearshore teams, Gorilla Logic has been instrumental in developing business-critical software applications for Fortune 500 and SMB companies for over 20 years. Their services include creating SaaS platforms, enhancing digital experiences, and providing flexible, security-focused solutions. Gorilla Logic operates with teams located in Costa Rica, Colombia, Mexico, and the United States, emphasizing collaborative partnerships to deliver cutting-edge digital engineering solutions.

📋 Description

• Design and build production-grade services, APIs, SDKs, internal tools, and reusable platform capabilities • Develop systems combining AI agents, tools, deterministic workflows, APIs, events, and human approval steps • Implement agent runtimes, model invocation, reusable skills, backend services, and automated actions • Build orchestration patterns involving routing, sequencing, parallel execution, delegation, retries, checkpoints, scheduling, memory, and state management • Integrate enterprise context through MCP, RAG, repositories, tickets, documents, databases, search systems, and APIs • Connect the Harness with GitHub, Azure DevOps, Jira, Slack, cloud services, SaaS products, and internal applications • Implement identity, permissions, policies, approval gates, guardrails, access controls, audit trails, and operational kill switches • Build observability for agent activity, distributed traces, logs, metrics, token consumption, model and tool calls, failures, latency, and cost • Create automated evaluations, benchmark datasets, regression suites, quality thresholds, hallucination checks, and model or prompt comparisons • Improve developer experience through APIs, SDKs, CLIs, templates, configuration systems, documentation, and reusable reference implementations • Build lightweight user interfaces, administrative tools, approval experiences, or operational dashboards when required • Deploy and operate solutions across AWS, Azure, or Google Cloud using containers, serverless services, CI/CD, infrastructure as code, IAM, networking, and secrets management • Conduct technical discovery in unfamiliar client environments and translate business and technical needs into scalable implementation patterns • Move from discovery and experimentation to working integrations and production-ready solutions • Communicate architecture decisions, risks, and trade-offs to client engineers, architects, product teams, and technical leadership

🎯 Requirements

• Senior-level experience designing, building, and operating production software systems • Deep expertise in at least one area of software engineering, such as backend, full-stack, frontend, platform, cloud, data, or quality engineering • Proficiency in one or more programming languages such as Python, TypeScript, JavaScript, Java, Kotlin, C#, or Go • Experience building APIs, services, enterprise integrations, or distributed systems • Understanding of asynchronous processing, events, state management, scalability, reliability, and architectural trade-offs • Experience with REST APIs, GraphQL, webhooks, message queues, databases, and authentication • Experience with at least one major cloud platform: AWS, Azure, or Google Cloud • Familiarity with containers, serverless computing, CI/CD, IAM, networking, storage, and secrets management • Working knowledge of LLM APIs, tool calling, structured outputs, embeddings, RAG, AI agents, and model selection • Understanding of when to use agents, deterministic workflows, automation, or traditional software components • Experience with SQL, data models, retrieval systems, indexing, or vector stores • Ability to troubleshoot systems across applications, infrastructure, APIs, data sources, and external integrations • Strong technical discovery, prototyping, problem-solving, and client-facing communication skills • Ability to work autonomously in environments with ambiguity and evolving requirements • Preferred: Experience building AI platforms, internal developer platforms, workflow systems, or enterprise automation solutions • Preferred: Experience with MCP, agent orchestration frameworks, multi-agent systems, or tool integration patterns • Preferred: Experience with Kubernetes, infrastructure as code, distributed tracing, or OpenTelemetry • Preferred: Experience building automated evaluations for AI agents, prompts, models, or retrieval systems • Preferred: Experience with modern frontend frameworks such as React, Angular, or Vue • Preferred: Experience creating SDKs, CLIs, templates, internal tools, or developer documentation • Preferred: Experience working directly with client engineering, architecture, security, or product teams