AI Engineer Developer

Role Description

Strong backend development experience in Python, TypeScript, Node.js, Java, Go, or similar.

Experience building APIs, workflow services, integrations, automation scripts, and event-driven applications.

Strong API integration skills: REST, GraphQL, webhooks, authentication, authorization, and scheduled automation jobs.

Hands-on experience with Slack apps, bots, APIs, or enterprise collaboration platform integrations.

Experience integrating with ticketing/workflow tools: Jira, Zendesk, ServiceNow, Confluence, or similar.

Experience with orchestration frameworks, workflow engines, agent runtimes, or stateful task execution.

Hands-on experience building GenAI applications, AI agents, RAG workflows, tool-calling systems, or chatbot platforms.

Experience with LLM APIs and GenAI platforms: OpenAI, Claude, ChatGPT Enterprise, Azure OpenAI, Amazon Bedrock, Google Vertex AI, Databricks, or similar.

Understanding of MCP concepts, tool registries, connector libraries, skill version management, and secure tool invocation.

Experience with prompt engineering, prompt versioning, structured outputs, function calling, JSON schemas, and agent guardrails.

Understanding of IAM concepts: Okta, SCIM, SSO, RBAC, ABAC, service accounts, secrets management, and enterprise governance requirements.

Ability to build secure, auditable, and reliable operational tooling for enterprise users.

Familiarity with logging, monitoring, tracing, metrics, dashboards, retries, error handling, operational observability, and incident troubleshooting.

Good knowledge of automated testing, CI/CD pipelines, deployment practices, release management, rollback strategies, and operational support processes.

Strong understanding of secure coding practices, data privacy, access controls, and enterprise governance standards.

Key Technical Skills

• Python
• TypeScript
• Node.js
• Java
• Go
• AI Agents & GenAI Applications
• RAG (Retrieval-Augmented Generation)
• LLM APIs (OpenAI, Claude, Azure OpenAI, Bedrock, Vertex AI)
• REST, GraphQL, Webhooks
• Workflow Orchestration & Agent Runtimes
• MCP (Model Context Protocol)
• Function Calling & Structured Outputs
• Prompt Engineering
• Slack Apps/Bots Integration
• Jira, Zendesk, ServiceNow, Confluence
• IAM (Okta, SSO, RBAC, ABAC)