Key skills
JavaScriptTypeScriptPythonAILLMOpenAILangChainAgenticAirflowGraphQLAWSAzureGCPTerraformKubernetesDockerGitHub ActionsAnsibleGitHubCI/CD
About this role
Alignerr is at the forefront of AI development, seeking an AI Automation & Tool Use Engineer to enhance agentic AI systems. The role involves designing and evaluating AI workflows, assessing AI-generated code, and providing expert feedback to improve AI reasoning and task-planning capabilities.
Responsibilities:
- Design, test, and evaluate agentic AI workflows involving tool use, API calls, and multi-step task execution
- Assess AI-generated code and automation pipelines for correctness, efficiency, and reliability
- Build and refine function-calling schemas, tool orchestration patterns, and integration architectures
- Identify failure modes, edge cases, and error-handling gaps in AI agent behavior
- Provide structured, expert feedback that directly improves AI reasoning and task-planning capabilities
- Work across real-world scenarios spanning DevOps, CI/CD, cloud infrastructure, data pipelines, and workflow automation
- Collaborate asynchronously with a global team on cutting-edge agentic AI projects
Requirements:
- 3+ years of professional experience in software engineering, DevOps, automation, or workflow design
- Strong familiarity with API integrations (REST, GraphQL, webhooks) and function-calling paradigms
- Experience with orchestration tools, automation frameworks, or infrastructure-as-code (e.g., Terraform, Ansible, GitHub Actions, Airflow, Zapier, or similar)
- Comfortable reading and writing code in Python, JavaScript/TypeScript, or other widely used languages
- Solid understanding of multi-step task execution, state management, and error handling in automated systems
- Strong analytical and problem-solving skills with sharp attention to detail
- Clear written communicator — able to articulate technical decisions and trade-offs concisely
- Self-motivated and comfortable working independently on flexible, task-based assignments
- Experience building or working with AI agents or LLM tool-use frameworks (e.g., LangChain, AutoGPT, CrewAI, OpenAI function calling)
- Background in cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
- Familiarity with prompt engineering or AI evaluation methodologies
- Experience designing developer tools, SDKs, or platform integrations