AI Engineer

Role Overview

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.

Key Responsibilities

• 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

Required Skills

• 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

Preferred Skills

• 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

Ideal Candidate

• 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