Sr AI Engineer - Need on W2

Required Qualifications

• 8+ years of software engineering, cloud engineering, platform engineering, DevOps, or infrastructure experience.
• 3+ years working with AI/LLM platforms, AI agents, copilots, or agentic systems.
• Strong cloud experience in AWS, Azure, or GCP.
• Hands-on Kubernetes administration and deployment experience.
• Strong Infrastructure as Code experience using Terraform.
• Experience with CI/CD pipelines and automated deployments.
• Strong understanding of networking, cloud architecture, security, and distributed systems.
• Experience implementing Identity and Access Management (IAM), RBAC, SSO, and secrets management.
• Experience integrating enterprise platforms through APIs and automation frameworks.
• Ability to read, understand, and modify existing deployment code and infrastructure configurations.
• Strong scripting and programming skills in at least one language such as:
• Python
• Java
• Go
• JavaScript/TypeScript
• C#
• Rust
• Other modern programming languages

Note: The primary requirement is strong engineering and coding ability. No specific programming language is required.

Preferred Qualifications

• Experience working with AI agent frameworks and open-source agent platforms.
• Experience with Hermes, Open WebUI, or similar AI gateway/orchestration platforms.
• Experience with AWS Kiro, GitHub Copilot, Claude Code, Cursor, Codex, or comparable AI engineering tools.
• Experience building agent integrations, tool-calling systems, MCP implementations, or workflow automation platforms.
• Familiarity with vector databases, RAG architectures, embeddings, and LLM orchestration frameworks.
• Experience designing secure multi-tenant cloud environments.
• Experience supporting enterprise-scale AI deployments.
• Experience collaborating with SRE and DevOps teams in production environments.