Senior GenAI Developer

Accenture is hiring a Senior GenAI Developer to build and deploy generative AI, retrieval, and agentic AI solutions for client business use cases. The role also develops enterprise data integrations and platform capabilities, and supports AI evaluation, governance, security, and production readiness.

Responsibilities:

• As an AI / ML Engineer, you will be responsible for developing applications and systems that utilize artificial intelligence tools and cloud artificial intelligence services, ensuring proper cloud or on-premises application pipelines with production-ready quality. Your work will involve applying generative artificial intelligence models as part of the solution, which may include deep learning, neural networks, chatbots, and image processing. You are expected to be a subject matter expert, collaborate and manage the team to perform effectively, take responsibility for team decisions, engage with multiple teams, contribute to key decisions, and provide solutions to problems within your immediate team and across multiple teams
• Design and develop GenAI applications leveraging FLARE platform capabilities
• Build conversational AI solutions using Large Language Models (LLMs)
• Develop AI-powered automation for document intelligence, commentary generation, validation workflows, and business insights
• Implement solutions using prompt engineering, prompt orchestration, and context management techniques
• Optimize AI applications for accuracy, performance, scalability, and cost efficiency
• Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories
• Implement document ingestion, chunking, metadata extraction, embedding generation, and retrieval pipelines
• Build and maintain Knowledge Bases supporting business-specific domains
• Develop semantic search and contextual information retrieval capabilities
• Improve response quality through tuning and evaluation of retrieval mechanisms
• Design and implement multi-agent workflows using frameworks such as LangGraph and MCP-based architectures
• Build intelligent agents capable of reasoning, tool selection, orchestration, and task execution
• Integrate agents with enterprise systems, databases, APIs, and business applications
• Develop reusable AI components and agent frameworks across FLARE use cases
• Develop integrations with:
• Oracle databases
• Starburst
• S3 repositories
• Internal data services
• Enterprise APIs
• Enable AI-driven analysis of both structured and unstructured data sources
• Build secure pipelines for ingestion and retrieval of business data
• Develop microservices and APIs supporting FLARE capabilities
• Implement scalable containerized applications on OpenShift
• Build automated deployment pipelines and CI/CD processes
• Improve platform reliability, observability, logging, and monitoring
• Collaborate with architects and platform engineers to enhance FLARE capabilities
• Develop testing frameworks for AI solutions
• Measure response quality using evaluation metrics and business validation criteria
• Support responsible AI practices, model governance, security, and compliance requirements
• Participate in AI risk reviews and production readiness assessments