We are looking for an AI Full-Stack / Systems Engineer to build scalable backend services and platform components that power enterprise AI applications and agent-based workflows.

The role focuses on LLM integrations, AI orchestration frameworks, RAG-based knowledge systems, and production-grade AI infrastructure used by multiple engineering teams.

This engineer will work closely with platform, architecture, and application teams to build secure, reliable, and governed AI systems at enterprise scale.

·      Build backend services supporting AI agents and multi-step AI workflows

·      Develop LLM integration layers and model service APIs

·      Implement RAG pipelines including document ingestion, embeddings, and vector retrieval

·      Build orchestration frameworks connecting models, tools, and enterprise APIs

·      Implement AI safety controls, guardrails, and policy enforcement

·      Develop observability, monitoring, and cost tracking for AI systems

·      Integrate AI systems with enterprise platforms and internal services

 

·      Strong backend engineering experience (Python preferred)

·      Experience building distributed systems / microservices

·      Hands-on experience with LLMs, RAG architectures, or AI agent frameworks

·      Experience integrating AI APIs such as OpenAI, Anthropic, Bedrock, etc.

·      Experience with cloud platforms (AWS preferred)

·      Familiarity with vector databases, embeddings, and knowledge retrieval systems

·      Experience with REST APIs, containerization (Docker), and modern backend frameworks

 

·      Experience with LangChain, LlamaIndex, or agent orchestration frameworks

·      Experience building AI platform components or internal developer platforms

·      Exposure to AI governance, guardrails, and evaluation frameworks

·      Experience operating systems in enterprise or regulated environments

·      5–10 years backend / platform engineering experience

·      Hands-on experience building production AI systems

·      Strong problem-solving and distributed systems background

Comfortable working in AWS cloud-native environments