Description

You will own the end-to-end design and delivery of production-grade agentic and Generative AI systems.

Responsibilities

• Architect robust systems for agentic workflows, GenAI/RAG pipelines, and evaluation frameworks.
• Optimize models for throughput, latency, and scaling across AWS infrastructure.
• Conduct deep-dive debugging and resolve critical production incidents, pairing with developers to improve code quality.
• Build reference implementations using frameworks like Semantic Kernel, LangGraph, AutoGen, or CrewAI.
• Deploy and manage services on AWS, enforcing SLIs/SLOs using observability tools.

Required Skills

• 7-10 years in software/AI engineering, including 4+ years in GenAI application development.
• Expert in Python 3.11+ (asyncio, typing, packaging, profiling, pytest).
• Hands-on experience with Semantic Kernel, LangGraph, AutoGen, or CrewAI.
• Proven delivery of GenAI/RAG systems on AWS Bedrock or equivalent vector platforms.
• Deep knowledge of the AWS ecosystem: EKS, Bedrock, S3, SQS/SNS, RDS, ElastiCache, IAM/Okta.
• Expertise in observability using OpenTelemetry and DataDog.
• Strong focus on cost, performance, and security engineering with a FinOps mindset.
• Experience with CI/CD practices, including GitHub Actions and Terraform.

Key Skills

Education

Any Graduate