Artificial Intelligence Consultant

THIS IS A LONG TERM CONTRACT POSITION WITH ONE OF THE LARGEST GLOBAL TECHNOLOGY LEADERS.
About the Role
Our client is looking for an experienced AI/ML Engineer to build enterprise-grade chatbots and intelligent assistants using state-of-the-art LLM and Generative AI technologies.
The role focuses on finance data, RAG-based architectures, hallucination mitigation, and agentic AI systems deployed at scale. You will collaborate closely with Product, Data, and Platform teams to deliver reliable, explainable, and production-ready AI solutions.
Minimum Qualifications
5–7 years of relevant professional experience in AI/ML Engineering.
Strong hands-on programming experience with Python and SQL.
Experience building LLM-powered applications, chatbots, or intelligent assistants.
Hands-on experience with RAG architectures, retrieval pipelines, embeddings, and vector databases.
Experience with LLMs such as OpenAI GPT, Anthropic, Gemini, or Llama.
Experience with agentic AI frameworks such as LangChain and/or LangGraph.
Understanding of tool calling, Agent-to-Agent (A2A) architectures, and multi-step AI workflows.
Experience implementing techniques to reduce LLM hallucinations, including grounding, re-ranking, citations, and confidence scoring.
Experience deploying and monitoring AI/ML applications using cloud and MLOps practices.
Hands-on experience with AWS services such as S3, EC2, ECS, Lambda, SageMaker, or CodePipeline.
Experience implementing CI/CD pipelines for AI/ML applications and inference services.
Experience working with structured and unstructured enterprise data.
Strong understanding of LLM evaluation, prompt/version management, and AI observability.
Key Responsibilities
Build LLM-powered chatbots and intelligent assistants using OpenAI, RAG, tool calling, and agent frameworks such as LangChain and LangGraph.
Design Agent-to-Agent (A2A) architectures for multi-step reasoning and autonomous workflows.
Design and implement retrieval pipelines using embeddings, vector databases, hybrid search, and cross-encoders.
Implement hallucination mitigation techniques including grounding, re-ranking, citations, and confidence scoring.
Work with finance and enterprise datasets while ensuring accuracy, reliability, and data governance.
Deploy, monitor, and operate AI systems using cloud-native and MLOps practices.
Implement and maintain CI/CD pipelines for AI pipelines and inference services.
Develop and maintain evaluation frameworks for measuring the quality and reliability of LLM applications.
Apply observability and evaluation tools such as LangSmith, MLflow, and Weights & Biases.
Work with data platforms and pipelines involving Snowflake, DBT, structured data, and unstructured data.
Collaborate with Product, Data, and Platform teams to deliver scalable, explainable, and production-ready AI solutions.
Our large, Fortune Technology client is ranked as one of the best companies to work with, in the world. As a global leader in 3D design, engineering, and entertainment software, they foster progressive culture, creativity, and a flexible work environment. They use cutting-edge technologies to keep themselves ahead of the curve. Diversity in all aspects is respected. Integrity, experience, honesty, people, humanity, and passion for excellence are some other adjectives that define this global technology leader.

Work arrangement
Hybrid