AI Engineer - Generative AI & Cloud Infrastructure

Role Overview

We are seeking a highly skilled AI Engineer – Generative AI & Cloud Infrastructure to design, build, and optimize large-scale LLM-based systems and cloud-native architectures. The ideal candidate will bring a strong background in Generative AI workflows (RAG, multi-agent systems), AWS cloud engineering, and secure, production-grade deployment of AI applications.

This is a hands-on engineering role that blends AI model orchestration, API development, and cloud infrastructure management, ensuring enterprise-grade scalability, security, and reliability.

Key Responsibilities

• Implement and manage LLM workflows such as Retrieval-Augmented Generation (RAG) and multi-agent pipelines.
• Orchestrate model interactions using frameworks like LangChain, LangGraph, or custom-built orchestration layers.
• Develop and maintain APIs for LLM endpoints, vector search, and tool-augmented responses.
• Integrate external tools (search engines, calculators, APIs) and manage agent memory (episodic and long-term).
• Build robust data ingestion pipelines and document loaders for diverse formats (PDF, HTML, slides, etc.).
• Implement efficient chunking and embedding strategies for retrieval optimization.
• Set up and maintain vector databases with metadata indexing and optimized search strategies.
• Ensure low-latency inference and high concurrency via caching, batching, and streaming.
• Monitor and optimize model performance for project-specific use cases.
• Utilize observability tools such as LangFuse, LangSmith, Arize, and PromptLayer to track LLM behavior and quality.
• Securely log prompts, responses, and monitor model quality and performance metrics.
• Implement security best practices—authentication, authorization, rate limiting, and API usage tracking (OpenAI, Bedrock, API Gateway).
• Apply enterprise safety frameworks for responsible AI deployment.
• Design and manage scalable, secure, and highly available cloud architectures using AWS services (EC2, S3, VPC, RDS, Lambda, SageMaker, OpenSearch, Bedrock, DynamoDB).
• Write and maintain application code integrating AWS SDKs and APIs.
• Configure networking components such as ALBs, Auto Scaling Groups, and Route 53.
• Deploy and scale workloads on ECS/EKS, with full observability and cost optimization.
• Troubleshoot infrastructure issues, optimize cloud performance, and ensure compliance with security standards.

Required Skills & Experience

• 10+ years of experience in AI Engineering, ML Ops, or Cloud Infrastructure roles.
• Strong programming skills in Python (preferred) or similar languages.
• Hands-on experience with LLM frameworks and GenAI orchestration tools.
• Deep expertise in AWS Cloud services and architecture design.
• Familiarity with observability tools for AI systems (LangFuse, LangSmith, etc.).
• Strong understanding of secure software development and enterprise-grade deployment.
• Proven ability to scale AI/ML workloads in production environments.