Role Objective
Responsible for analyzing, designing, developing, maintaining, and ensuring the quality, reliability, and observability of artificial intelligence agents implemented in Python, within a previously defined architectural framework. This is a highly hands-on role, execution-focused, with technical autonomy to define agent behavior, flows, orchestration, and tools, while supporting and guiding other team members when required.
Key Roles, Responsibilities, and Functions
Implement AI agents primarily in Python, following established architectural principles and guidelines
Translate product requirements and workflow definitions into concrete agent behaviors
Design and implement agent flows based on graphs, state machines, and/or tool-based orchestration frameworks
Define and develop state transitions, error handling, retries, and failure recovery mechanisms
Integrate agents with internal tools, APIs, external services, and structured data sources
Ensure agents are observable, testable, and production-ready (logs, metrics, traces)
Design and implement unit tests, integration tests, and agent behavior tests
Verify correct execution of automated tests and keep them aligned with code evolution
Collaborate with product, platform, and architecture teams to validate assumptions and technical decisions
Rapidly iterate on agents based on real usage, feedback, and operational metrics
Document technical and process-related aspects (agent flow diagrams, technical decisions, README files, internal documentation)
Actively participate in code reviews and serve as a technical reference for best practices
Define and adhere to quality standards, maintainability, and code structure related to agent development
Key Accountability Areas
Achievement of technical and delivery objectives
Correct and stable implementation of AI agents in production
Code quality, maintainability, and clarity of Python code
Observability and reliability of agent behavior
Compliance with service-level agreements
Effective collaboration with internal teams and stakeholders
Academic Background
Technical degree or Bachelor’s degree in Computer Engineering, Computer Science, Software Engineering, or related fields, or equivalent knowledge demonstrated through professional experience.
Language
Technical and conversational English, minimum B2+ level according to the Common European Framework of Reference (CEFR).
Core Competencies
Connection, vision, empowerment, technical judgment, and initiative.
(Expected behaviors for each competency are defined internally.)
Professional Experience and Technical Skills
Minimum of 5 years of experience developing production-grade software systems
Strong experience with Python for backend or systems development
Hands-on experience building LLM-based agents or complex language-model-driven workflows
Experience with agent orchestration frameworks based on graphs or state machines (e.g., LangGraph or similar)
Experience integrating LLMs with tools, APIs, and structured data
Ability to work within clearly defined architectural constraints
Strong debugging and observability mindset (logs, metrics, traces)
Quality Assurance and Best Practices
Best development practices for efficiency, quality, and maintainability
Structured error handling and retry mechanisms
Technical documentation (diagrams, README files, agent flows)
Integration and Architecture
Integration of software services and components
REST APIs
Real-time data handling
Experience working alongside service-oriented backend systems (including Java ecosystems or others)
Platforms, Tools, and Technologies
Proficiency with *nix shells (bash, sh, zsh, etc.)
Git
Branching strategies (GitFlow, trunk-based development, etc.)
CI/CD tools (GitHub Actions, GitLab CI, etc.)
Containers (Docker, Podman, etc.)
Cloud computing services (AWS, GCP, Azure, etc.)
Languages and Runtimes
Programming languages (at least one):
Python (required)
JavaScript / TypeScript (preferred)
Runtime platforms:
CPython
Preferred Experience / Bonus
Experience with AgentCore or other managed agent runtimes
Experience with multiple agent frameworks (LangChain, AutoGen, CrewAI, Strands, etc.)
Design of deterministic flows combined with open-ended reasoning
Session management, memory handling, and summarization patterns
Experience with async Python, concurrency, or event-driven systems
Benefits
Edify is proud to be an equal-opportunity employer committed to diversity and inclusion. We encourage all candidates to apply regardless of their sex, gender identity, sexual orientation, race, color, religion, national identity, disability, age, medical condition, pregnancy, marital status, family status or any other characteristic protected by law.
Hello, we are Edify, one of the highest-ranked IT companies in Costa Rica and Central America.We're a consolidated technology services consulting firm specializing in education technology. We deliver unbelievably creative and rock-solid solutions for a wide range of clients, including major corporations, startups, educational institutions, and non-profit organizations.We help our clients design, build and run some of the most interesting ventures in the industry while promoting a warm, friendly and cooperative culture. Work and life should definitely be balanced, so we're serious about cultivating a great work environment.
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