Senior Agentic AI Engineer

Posted 2 Days Ago
Be an Early Applicant
11 Locations
Remote
Senior level
Artificial Intelligence • Cloud • Professional Services • Software
The Role
Design, build, deploy, and scale production-ready autonomous AI agents and multi-agent workflows on AWS. Develop RAG pipelines, MCP integrations, vector database solutions, evaluation frameworks, observability, security controls, and human-in-the-loop guardrails. Lead cloud architecture, mentor nearshore engineering teams, optimize LLM application reliability, and communicate technical architecture to stakeholders.
Summary Generated by Built In
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.

Skills Required

  • 5+ years of professional software engineering experience
  • 2–3+ years of LLM application engineering and agentic AI systems experience
  • Advanced Python experience
  • AWS and Amazon Bedrock experience
  • Experience with LangGraph, CrewAI, or Agent Development Kit
  • Experience with Pinecone or Weaviate vector databases
  • Retrieval-Augmented Generation architecture experience
  • Model Context Protocol integration experience
  • Hands-on experience with LangSmith, Langtrace, or AgentOps
  • Experience with evaluation frameworks for LLM groundedness and accuracy
  • Advanced written and spoken English
  • Ownership mindset, technical leadership, and mentoring ability
  • Reinforcement learning and advanced multi-agent coordination experience
  • Experience with Chainlit, Streamlit, or React
  • Multicloud experience with Azure AI or Google Cloud Platform
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The Company
350 Employees
Year Founded: 2002

What We Do

CodeRoad is a nearshore software development and technology-execution partner that helps organizations modernize applications, migrate to the cloud, build digital products, and implement enterprise AI. Its services span the full software development lifecycle, including dedicated engineering teams, platform engineering, data and AI infrastructure, legacy modernization, cloud architecture, quality automation, and DevOps. The company serves startups, enterprises, and private-equity portfolio businesses.

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