Senior GenAI Developer

Accenture Flex offers you the flexibility of local fixed-duration project-based work powered by Accenture, a leading global professional services company. Accenture is consistently recognized on FORTUNE's 100 Best Companies to Work For and Diversity Inc's Top 50 Companies For Diversity lists.

As an Accenture Flex employee, you will apply your skills and experience to help drive business transformation for leading organizations and communities. In addition to delivering innovative solutions for Accenture's clients, you will work with a highly skilled, diverse network of people across Accenture businesses who are using the latest emerging technologies to address today's biggest business challenges.

You will receive competitive rewards and access to benefits programs and world-class learning resources. Accenture Flex employees work in their local metro area onsite at the project, significantly reducing and/or eliminating the demands to travel.

Key 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. Expert proficiency in Agentic Design is required. Expert proficiency in Python Development, Retrieval-Augmented Generation is recommended. Expert proficiency in Large Language Model (LLM) Fine-Tuning, along with advanced proficiency in AI Agents, Prompt Engineering, and Vector Databases, is suggested.

Generative AI Solution Development

• 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.
• RAG and Knowledge Base Engineering
• 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.

Agentic AI Development

• 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.

Enterprise Data Integration

• 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.

Platform Engineering and Development

• 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.

AI Evaluation and Governance

• 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.

Must be willing to be onsite up to 4 days per week onsite with the client in Charlotte, NC, Plano, TX or Jersey City, NJ. 5 days away per quarter is also required by the client.