Job Description & How to Apply Below
THIS IS A 6-MONTH CONTRACT POSITION WITH ONE OF THE LARGEST GLOBAL TECHNOLOGY LEADERS.
We are looking for a highly skilled LLM / Agentic AI Engineer to design and build production-grade AI systems powered by Large Language Models. You will architect intelligent, multi-agent workflows, implement advanced RAG pipelines, and deploy enterprise-ready AI solutions working with finance and large-scale datasets.
This role requires strong expertise in LLM engineering, retrieval systems, agent orchestration, and cloud-native deployment practices.
Primary Skills - AI/ML, LLM, Python, Snowflake/SQL
Secondary Skills - Agentic AI, MCP
Qualifications
- 3+ years of relevant experience in AI/ML or applied LLM engineering.
- Strong hands-on experience with Python and SQL (Snowflake preferred).
- Proven experience building LLM-powered applications using OpenAI (GPT-4/4.1), Anthropic, Gemini, or Llama models.
- Experience implementing RAG pipelines including embeddings, chunking strategies, hybrid search, and vector databases.
- Hands-on experience with Lang Chain, Lang Graph, tool calling, and agent frameworks.
- Solid understanding of hallucination mitigation techniques including grounding, re-ranking, citations, and confidence scoring.
- Experience working with structured and unstructured enterprise datasets.
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
Preferred Qualifications
- Experience designing Agent-to-Agent (A2A) architectures for multi-step reasoning and autonomous workflows.
- Hands-on experience with MCP (Model Context Protocol) and agent memory/state management.
- Experience using evaluation and observability tools such as Lang Smith, MLflow, or Weights & Biases.
- Strong understanding of prompt/version management and offline/online LLM evaluation techniques.
- Experience deploying AI systems on AWS (S3, Lambda, Sage Maker, Bedrock).
- Experience implementing CI/CD pipelines for AI inference services and model workflows.
- Exposure to DBT and modern data transformation pipelines.
- Experience building scalable, monitored, and cost-optimized AI systems in production environments.
Responsibilities
- Design and build LLM-powered chatbots and AI applications using OpenAI APIs, RAG pipelines, and agent frameworks.
- Architect and implement multi-agent (A2A) systems for complex reasoning and workflow automation.
- Design and optimize retrieval systems using embeddings, hybrid search, and vector databases.
- Implement techniques to reduce hallucination and improve output reliability through grounding and evaluation frameworks.
- Work with finance and enterprise data ensuring accuracy, governance, and compliance.
- Deploy, monitor, and optimize AI systems using cloud-native infrastructure and MLOps best practices.
- Implement CI/CD pipelines for AI workflows and inference services.
- Continuously evaluate and improve prompt performance, model responses, latency, and cost efficiency.
About the Client
Our client is a Fortune-ranked global technology leader, renowned for innovation and engineering excellence.
They foster a culture of collaboration, technical depth, and continuous learning, empowering engineers to build next-generation solutions that impact millions of users worldwide.
The organization values integrity, diversity, and curiosity, creating an environment where technology professionals can thrive and innovate freely.
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