---
title: 'Senior Agentic AI Engineer at CodeRoad'
canonical: 'https://feeny.ai/job/senior-agentic-ai-engineer-coderoad-latin-america-70cdthm40395'
type: 'job'
last_seen: '2026-09-17'
---

# Senior Agentic AI Engineer at CodeRoad

- **Company:** CodeRoad
- **Location:** Latin America
- **Work type:** remote
- **Posted:** 2026-08-19
- **Last confirmed live:** 2026-09-17
- **Apply:** https://job-boards.greenhouse.io/coderoad/jobs/4375543009

## Job description

## About CodeRoad

CodeRoad provides end-to-end software development services, helping businesses scale with ideal infrastructure solutions. From staff augmentation to dedicated IT teams and general software engineering, our nearshore technology services empower businesses to thrive in an ever-evolving digital landscape

## About the Role

As a Senior Agentic AI Developer, you will serve as the technical backbone of our AI engineering initiatives, designing, building, and deploying production-ready AI agents and agentic workflows. You will architect autonomous systems leveraging cutting-edge LLM frameworks, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP) to seamlessly connect AI agents with complex enterprise infrastructures and data ecosystems.

This role is critical to transforming business requirements into scalable, secure, and highly reliable agentic solutions on AWS. You will anchor technical execution and architectural strategy, establishing robust evaluation, observability, and human-in-the-loop guardrails while guiding nearshore development teams through the entire lifecycle of production AI deployment.

## Key Responsibilities

- Architect & Build: Design, develop, and scale autonomous agentic workflows and multi-agent systems using LangGraph, CrewAI, or Agent Development Kit (ADK).

- Anchor Cloud Infrastructure: Own the cloud deployment and security architecture of LLM-powered applications on AWS, using Amazon Bedrock and scalable microservices.

- Integrate & Orchestrate: Connect AI agents to enterprise APIs, data sources, and deterministic tools via Model Context Protocol (MCP) and workflow platforms like n8n.

- Optimize Knowledge Systems: Build high-performance RAG pipelines and vector database integrations using Pinecone or Weaviate to optimize contextual retrieval and reranking.

- Evaluate & Secure: Implement end-to-end evaluation, guardrails, and security measures—including task-success metrics, hallucination checks, and protection against prompt injection.

- Monitor & Mentor: Lead system observability using tools like LangSmith, Langtrace, or AgentOps while mentoring engineering PODs in Python and AI development best practices.

## Requirements

- Experience: 5+ years in professional software engineering, with 2–3+ years dedicated to LLM application engineering and agentic AI systems.

- Tech Stack: Advanced Python, AWS (Amazon Bedrock), LangGraph / CrewAI, Vector DBs (Pinecone, Weaviate), RAG architecture, and MCP integration.

- Observability & Eval Tools: Hands-on experience with LangSmith, Langtrace, or AgentOps, along with evaluation frameworks for LLM groundedness and accuracy.

- Soft Skills: Strong ownership mindset, technical leadership, and the ability to mentor developers and articulate complex architecture to non-technical stakeholders.

- Language Skills: Advanced English (written and spoken) is mandatory.

## Nice to Have

- Exposure to reinforcement learning and advanced multi-agent coordination architectures.

- Hands-on experience building user-facing AI interfaces with Chainlit, Streamlit, or React.

- Multicloud experience with Azure AI or Google Cloud Platform (GCP).

## What You’ll Love

- 100% Remote: Work from anywhere in Latin America.

- Holidays Off: Observe local national holidays.

- Paid Time Off: Generous PTO policies for rest and personal time.

- Health Insurance Assistance: Financial support for your healthcare coverage.

- Competitive USD Compensation: Earn top-tier market rates pegged to the US Dollar.

- Growth Opportunities: Continuous career evolution within high-impact global projects.

## About CodeRoad

## Company Overview
- **One-liner**: CodeRoad is a next-generation technology execution partner that delivers nearshore software development, AI engineering, and digital transformation services through its Velocity-as-a-Service™ model.
- **Entity Type**: Private (bootstrapped / internally funded – no external funding rounds publicly disclosed)
- **Headquarters**: Not publicly disclosed; delivery hubs across 14 countries in Latin America with US-based leadership team. First delivery center opened in La Paz, Bolivia (2008).
- **Founded**: 2002
- **Founders**: Not publicly named; leadership team includes Dennis Odishoo (CEO & Partner), Todd Workman (COO & VP of Sales), Marcelo Schenone (VP of Delivery & Engineering), and Jess Young (Director of People & Culture).

## Core Business
- **Primary industries**: Software engineering services, AI engineering, digital transformation consulting, nearshore outsourcing.
- **Target customers**: Enterprise and mid-market companies (B2B) across luxury retail, financial services, automotive, and enterprise software.
- **Mission**: “Empower organizations to accelerate technology delivery through AI-ready systems and end-to-end software solutions that foster innovation, seamless integration, and measurable business impact.”

## Products & Services
- **Velocity-as-a-Service (VaaS)**: Outcome-based delivery model combining elite nearshore engineers, AI-powered development systems, and senior-led delivery pods. Measures success through execution performance and business value, not just staffing.
- **AI Engineering**: AI readiness assessments, agentic workflows, production deployment of AI/ML models, and AI-native delivery – built with secure-by-design governance (SOC2, HIPAA, PCI-DSS).
- **Nearshore Software Development**: Senior-led pods operating in U.S. time zones, providing full-stack, backend, frontend, mobile, DevOps, data engineering, and QA automation.
- **Digital Transformation**: Modernization of legacy systems, platform migration, and strategic execution of large-scale transformation programs with embedded architects and product leaders.

## Market Standing
- **Valuation / Funding**: Not publicly available (no disclosed valuation or funding rounds).
- **Key Metrics**: 
  - Client satisfaction rating: 4.8/5
  - Client retention: over 80% of clients stay beyond 5 years
  - 20+ years of SDLC execution experience
  - Delivery footprint across 14 Latin American countries
- **Notable Clients / Partners**: Historical clients include GM, Ford, and Whirlpool (from early supply chain platform). Current clients span luxury retail, financial services, automotive, and enterprise software (specific names not disclosed).
- **Growth Signals**: 
  - 36 active job openings as of July 2026 (Senior AI Engineer, MLOps, Delivery Director, etc.)
  - Expanding AI engineering and agentic workflow capabilities
  - Nearshore 3.0 model embedding talent, product leadership, and delivery accountability

## Competitive Advantages
- **Velocity-as-a-Service™ model** – moves from hiring to active production in weeks, not months, with outcome-based accountability.
- **Nearshore advantage** – LATAM engineers aligned to U.S. business hours, same time zone, cultural alignment, and cost efficiency.
- **Senior-led delivery pods** – experienced engineering leaders co-own delivery outcomes, not just staff augmentation.
- **Secure-by-design** – SOC2, HIPAA, and PCI-DSS built into architecture from day one, eliminating costly compliance retrofits.
- **Long-term partnerships** – over 80% retention for 5+ years demonstrates trust and consistent value delivery.
- **AI-powered SDLC** – agentic AI embedded into workflows, multi-agent systems for automation, and real-time performance dashboards.

## Strategic Focus
- Scaling the Velocity-as-a-Service model as the primary go-to-market offering.
- Deepening AI engineering capabilities (agentic workflows, production AI deployments, ML pipelines).
- Expanding nearshore delivery capacity across more LATAM countries while maintaining senior talent density.
- Helping enterprise clients move from AI experimentation to measurable business outcomes.
- Continuing to differentiate from traditional staff augmentation by embedding product leadership and delivery accountability.

## Why Work Here
- **Remote-first work model** – engineers can work from home across Latin America.
- **Competitive compensation**: Salaries paid in USD, plus health insurance assistance, paid vacation/holidays.
- **Career growth & learning**: Quarterly bootcamps, tech summits, mentorship programs, training and educational reimbursement.
- **High-impact projects**: Work on complex, real-world challenges for global industry leaders, building AI systems and modern platforms.
- **Culture**: “People-first” environment with a diverse global team, emphasis on collaboration and continuous innovation.
- **Senior talent density**: Opportunity to work alongside experienced engineering leaders and product managers.
- **Work schedule**: Aligned to U.S. business hours, enabling close collaboration with North American teams.

## Sources
1. [coderoad.com](https://coderoad.com/)
2. [coderoad.com/about-us](https://coderoad.com/about-us)
3. [coderoad.com/careers](https://coderoad.com/careers)
4. [job-boards.greenhouse.io/coderoad](http://job-boards.greenhouse.io/coderoad)
5. [linkedin.com/company/coderoad-inc](https://www.linkedin.com/company/coderoad-inc)

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