Senior AI Engineer - Agent Implementation

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

Qualifications

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

• Code testing, linting, and static analysis
• Design patterns applied to agent flows and behavior

• 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

Additional Information

Benefits

• 100% work remote from any part in Costa Rica.
• Digital Nomad.
• Monthly Internet connectivity allowance.
• Private health insurance for employees (90/10), 50% for beneficiaries (spouse and children).
• International Health Insurance.
• Marriage leave.
• Bereavement leave.
• Sick days.
• Ergonomic equipment.
• Educational assistance (courses, certifications, books).
• Life insurance for employees.
• $800 referral bonus.
• Personal support through our wellness department.
• Dental insurance.
• Optical insurance.
• Snacks and beverages if you want to work at the office.
• Free Parking.
• Meal allowance if you want to work at the office.
• Flex time
• Our Career Development Manager ensures ongoing, tailored support for each employee’s growth and career progression.
•  We reward the impact that goes beyond the expected — through “Good Vibes Great Impact”, our peer recognition program that celebrates meaningful contributions.
• Good times and a sense of community—that’s what our team building activities are all about.

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.