We are seeking talented Generative AI Engineers to join our team and build AI solutions that transform how our clients leverage artificial intelligence. In this role, you'll work at the intersection of software engineering and AI, designing and implementing sophisticated generative AI systems that go beyond simple API integrations. You'll be responsible for architecting scalable AI applications using cutting-edge platforms (such as AWS Bedrock, Gemini, OpenAI SDK, among others), building RAG (Retrieval-Augmented Generation) pipelines, implementing agentic architectures, and creating intelligent solutions that drive real business value.

As a Generative AI Engineer, you'll collaborate with cross-functional teams including product managers, data scientists, solution architects, and other engineers to translate complex business requirements into production-ready AI systems. Your work will directly impact product capabilities, user experience, and our clients' ability to innovate with AI technology.

AI Solution Development & Architecture

• Design, develop, and deploy production-ready applications using Large Language Models (LLMs), including GPT, Gemini, Claude and other foundation models through AWS Bedrock

• Build and optimize sophisticated RAG (Retrieval-Augmented Generation) architectures that can process and retrieve information from large-scale document repositories

• Implement and orchestrate multi-agent AI systems using AWS Bedrock Agents and AgentCore frameworks

• Design scalable AI pipelines that integrate with enterprise systems and maintain performance at production scale

Backend & Infrastructure Development

• Develop robust backend services and APIs for AI applications using Python and modern frameworks

• Implement containerization and deployment strategies for AI applications

• Build monitoring and observability solutions to track AI system performance, quality, and costs

Prompt Engineering & Model Optimization

• Design and optimize high-quality prompts and templates that guide LLM behavior and responses

• Implement advanced prompt engineering techniques to maximize model performance and accuracy

• Evaluate and fine-tune models for specific use cases when appropriate

• Continuously experiment with different model configurations, hyperparameters, and architectures

Collaboration & Innovation

• Partner with vertical areas and stakeholders to understand requirements and translate them into technical solutions

• Stay current with the latest advancements in generative AI research and evaluate emerging foundation models

• Contribute to technical documentation, best practices, and knowledge sharing within the team

• Participate in Sales initiatives related to Generative AI

Prefered Skills

• Strong years of professional software engineering experience

• Full-stack development experience

• Hands-on experience with

  • Large Language Models (LLMs) and foundation model APIs

  • Agentic Architecture & Implementation (e.g., LangChain, LlamaIndex, CrewAI, AutoGen)

  • Prompt engineering and optimization techniques

  • Data consumption for agentic with Vector databases (e.g., Pinecone, Weaviate, OpenSearch) and embedding models or Knowledge Graph

• Knowledge of DevOps practices and CI/CD pipelines for AI applications

• Knowledge of Python with experience in modern frameworks and libraries