[Job - 27329] Master Developer - Generative AI

We are tech transformation specialists, uniting human expertise with AI to create scalable tech solutions. With over 8,000 CI&Ters around the world, we’ve built partnerships with more than 1,000 clients during our 30 years of history. Artificial Intelligence is our reality. About the Role 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 What You'll Do 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 Qualifications Prefered Skills 3+ years of professional software engineering experience Full-stack development experience Hands-on experiencewithLarge Language Models (LLMs) and foundation model APIsAgentic Architecture & Implementation (e.g., LangChain, LlamaIndex, CrewAI, AutoGen)Prompt engineering and optimization techniquesData 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 Soft Skills & Mindset Explorer profile with genuine curiosity about AI and emerging technologies Resilience and adaptability when facing technical challenges and ambiguous problems Strong problem-solving abilities and analytical thinking Excellent communication skills to explain complex technical concepts to diverse audiences Collaborative mindset with the ability to work effectively in cross-functional teams What Sets You Apart You don't just integrate APIs—you understand model architectures and can make informed decisions about when to use different approaches You can balance innovation with pragmatism, knowing when to use cutting-edge techniques vs. proven solutions You think holistically about AI systems, considering performance, cost, security, and user experience You're comfortable with rapid iteration and learning from both successes and failures You can navigate ambiguity and thrive in fast-paced, evolving technology landscapes