CGI - Artificial Intelligence Engineer

Description:

- Design, build, and maintain LLM-powered applications, including chatbots, autonomous agents, and decision-support tools.

- Develop and optimize RAG pipelines using vector databases, embeddings, metadata filtering, and document preprocessing.

- Implement workflow orchestration using LangGraph, including event-driven agents, state management, and multi-step AI reasoning.

- Build AI solutions using LangChain components such as chains, tools, agents, memory, and custom integrations.

- Develop Agentic AI systems capable of multi-step task execution, planning, and reasoning.

- Write clean, scalable Python code for model serving, data processing, and API integrations.

- Fine-tune models, evaluate LLM outputs, and ensure reliability, grounding, and safety.

- Integrate AI systems with existing backend services, cloud platforms, and product architectures.

- Collaborate with ML engineers, data engineers, and product teams to deliver production-quality solutions.

- Monitor, evaluate, and optimize model performance, latency, and retrieval quality.

Required Skills & Qualifications:

- Hands-on experience with LangChain (chains, agents, tools, retrieval, memory).

- Strong understanding of LangGraph workflows and agent orchestration.

- Deep understanding of LLMs, embeddings, tokenization, prompt engineering, and evaluation.

- Experience building Agentic AI architectures (planning, reasoning, multi-agent workflows).

- Familiarity with LLM APIs (OpenAI, Anthropic, Groq, HuggingFace, etc.).

- Knowledge of REST APIs, microservices, and backend integration.

- Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker).

- Strong debugging, problem-solving, and algorithmic thinking skills.