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AI / Machine LearningRemote

Forward Deployed Engineer

AKAASA Technologies - Company

US, ๐Ÿ‡บ๐Ÿ‡ธ United StatesFull-time - Senior (4-7 years)0 applicantsCloses Aug 6, 2026

Salary

USD 236,581 - 236,581 / year

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Job description

Job details

  • Location: US
  • Work mode: Remote
  • Employment type: Full-time (Not an internship)
  • Salary: USD 236,581 per year

Role overview

AKAASA Technologies is looking for a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. This role focuses on implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions to solve complex business problems.

Job details

This is a Full-time, 100% Remote position based in the US. This is not an internship. The offered salary for this role is 236,581 USD.

Responsibilities

  • Design and implement sophisticated AI agents and agent-based workflows for enterprise use.
  • Develop scalable cloud-native services using microservices architecture and containerization.
  • Implement Retrieval-Augmented Generation (RAG) to enhance AI system accuracy and context.
  • Build and maintain orchestration workflows to streamline AI deployment and execution.
  • Collaborate with enterprise clients to deploy production-grade AI systems in their environments.

Requirements

  • Proven experience as a Software Engineer with a focus on AI-native application development.
  • Strong proficiency in building scalable microservices and cloud-native architectures.
  • Hands-on experience with RAG and LLM orchestration frameworks.
  • Expertise in containerization technologies such as Docker and Kubernetes.
  • Ability to work independently in a fully remote environment across the US.

Benefits

  • Competitive annual salary of 236,581 USD
  • 100% remote work flexibility
  • Opportunity to work with cutting-edge AI technologies
  • Professional growth in a high-impact engineering role

Keywords

AI AgentsRAGMicroservicesCloud NativePythonLLM OrchestrationDockerKubernetes