AI Native Software Engineer

I’m helping Quantum Wave Technologies, Inc find a top candidate to join their team full-time for the role of AI Native Software Engineer.

You'll architect and deploy cutting-edge agentic AI systems, transforming enterprise workflows.

Compensation:

Provide your expected compensation while applying

Location:

Remote: United States

Mission of Quantum Wave Technologies, Inc:

"To deliver high-impact SAP solutions and certified talent that help businesses transform, scale, and operate more efficiently."

What makes you a strong candidate:

• You have +8 years experience in Software engineering.
• You are proficient in Terraform, Python, Microservices, Kubernetes, Java.
• English - Conversational

Responsibilities and more:

My client is looking for multiple AI Native Software Engineers to support our client's growing AI practice.

Key Qualifications:

- Communicate clearly, deeply technical, and hands-on.

- Use GCP/Microsoft/Databricks.

- Use OpenSource scaffolding around AI models.

- Very heavy niche engineering skillset.

- Exceptional at amplifying productivity but still need to do review/validation of code.

- Have the agentic AI architecture built out (OpenAI/Cloud/GCP/Gemini/Databricks/AWS/Azure).

- Need production experience and Agentic AI experience, but doesn't need to have agentic AI production experience.

What You Must Have:

- 8+ years of software engineering experience.

- Strong experience with cloud-native systems (APIs, microservices, containers, serverless).

- Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration).

- Proficiency in Python, Java, or similar backend languages.

- Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar).

- Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI).

- Experience designing multi-agent or distributed AI systems.

- Familiarity with enterprise-scale system integration.

- Experience optimizing AI workloads for cost and performance.

Responsibilities Will Include:

- Design and implement AI agents, including Retrieval (RAG).

- Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models).

- Microservices architecture.

- Containers (Docker, Kubernetes).

- Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm).

- Build and deploy AI-powered applications aligned to business workflows.

- Integrate AI systems into existing enterprise platforms and APIs.