Description

Key Skills: Python, REST APIs, CI/CD, Generative AI, LLM Systems, RAG, Vector Databases, AWS Bedrock, SageMaker, Observability

Good to Have Skills: Experience supporting enterprise AI platforms or shared AI services, exposure to Copilot-style or workflow automation solutions, familiarity with Responsible AI principles and governance, experience working with cross-functional or client-facing teams, automated testing, distributed systems fundamentals, embeddings, prompt engineering, LLM evaluation, agentic and multi-agent workflows, monitoring and performance tuning.

Roles & Responsibilities:

• Design and build LLM-based systems using Retrieval Augmented Generation, embeddings, vector search, and prompt engineering techniques.
• Develop AI systems that integrate LLMs with REST APIs, enterprise systems, data platforms, and workflows for production use.
• Apply LLM evaluation techniques to assess quality, reliability, safety, and performance of AI systems in production environments.
• Own the full lifecycle of AI solutions from prototype to production including building, deploying, and operating AI workloads.
• Build and deploy AI workloads in AWS environments ensuring production readiness with focus on scalability and reliability.
• Implement CI/CD pipelines, automated testing, and versioning systems specifically designed for AI and machine learning workflows.
• Apply strong software engineering and distributed systems principles to AI development and production deployment processes.
• Implement comprehensive observability practices including logs, metrics, traces, and alerts for AI system monitoring.
• Monitor model behavior, system health, latency, and failures in production environments to ensure optimal performance.
• Work closely with AI engineers, data scientists, platform teams, and business stakeholders on cross-functional projects.
• Contribute to building and scaling AI platforms and reusable components for enterprise-wide AI initiatives.
• Share knowledge and mentor junior engineers on Generative and Agentic AI best practices and implementation strategies.

Experience Required: 5-7 years of experience in AI engineering and software development with focus on production AI systems

Key Skills

Education

Any Graduate