AI Engineer – Generative AI / LLMs / RAG

We are looking for an AI Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. You will design, build, and deploy intelligent applications such as chatbots, copilots, and AI-powered automation tools. This role combines software engineering, machine learning, and prompt/context engineering to deliver scalable, production-ready AI systems.

Key Responsibilities

Design and implement AI-powered applications using LLMs (OpenAI, Anthropic, open-source models, etc.)

Build and optimize RAG pipelines (vector databases, embeddings, retrieval strategies)

Develop chatbots and conversational AI systems with strong context management

Implement prompt engineering and context engineering strategies for reliable outputs

Integrate LLMs into backend systems via APIs and microservices

Work with vector databases (Pinecone, Weaviate, FAISS, etc.)

Optimize performance, latency, and cost of AI systems

Evaluate model outputs and implement guardrails (safety, hallucination reduction)

Collaborate with product and engineering teams to define AI features

Deploy and monitor AI services in cloud environments (AWS, Azure, GCP)

Required Qualifications

Strong programming skills in Python (preferred) or similar languages

Experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.)

Solid understanding of RAG architectures and embeddings

Experience building APIs and scalable backend systems

Familiarity with prompt engineering and evaluation techniques

Understanding of vector search and semantic retrieval

Experience with cloud platforms and containerization (Docker, Kubernetes is a plus)

Preferred Qualifications

Experience with fine-tuning or adapting LLMs

Knowledge of transformers and NLP fundamentals

Experience with agent-based systems or tool-using LLMs

Familiarity with ML Ops / LLM Ops practices

Experience with real-time conversational systems

Exposure to evaluation frameworks (RAG eval, LLM benchmarking)

Nice to Have

Experience with multi-modal models (text, image, audio)

Knowledge of knowledge graphs or hybrid retrieval systems

Your life at Accenture

At Accenture, we prioritize your health and well-being through comprehensive health insurance coverage and inclusive work arrangements. We value your growth and offer diverse learning and development paths, along with performance-based rewards. You'll also have access to resources for mental health and physical wellness, ensuring inclusivity and support. We provide additional financial support, flexible benefits, and care for your loved ones, respecting diverse circumstances.

Join us for a fulfilling career and a balanced lifestyle that celebrates diversity and promotes inclusivity.

The position is available exclusively for collaboration under an individual working contract (CIM).