AI Engineer
Role details
Job location
Tech stack
Job description
Artificial Intelligence Business Transformation Named Entity Recognition Critical Illness Insurance Python (Programming Language) Retrieval Augmented Generation PyTorch (Machine Learning Library) Artificial Intelligence Infrastructure Application Programming Interface (API) Applications Of Artificial Intelligence Machine Learning Model Monitoring And Evaluation, This role will focus on creating, reviewing, validating, and maintaining AI Systems that will also have maintain high-quality labeled datasets used to train and evaluate machine learning models across multiple domains including NLP, information retrieval, entity extraction, routing/classification, semantic search, and AI orchestration systems.
This contractor will work closely with data scientists, ML engineers, and AI platform teams to improve model quality, reliability, evaluation rigor, and production readiness., * retrieval quality, latency, and response accuracy through tuning and experimentation.
-
evaluation frameworks for RAG systems, including retrieval metrics, grounding quality, and factual consistency.
-
Identify and mitigate issues such hallucinations, context drift, tool routing errors, and retrieval gaps.
-
Collaborate with product and platform teams to deploy scalable, production-grade AI solutions.
-
Annotate and label datasets to support model training, evaluation, and alignment workflows.
Requirements
Github PySpark VS Code Metadata Chunking Debugging LangChain AI Safety Semantics Langgraph Operations Leadership Management LlamaIndex Agentic AI Scalability Benchmarking Tool Calling Deep Learning Hallucinations Problem Solving Network Routing Semantic Search Vector Database Computer Science Machine Learning Agile Methodology Unstructured Data Business Valuation Course Evaluations Prompt Engineering Workflow Management Information Retrieval Packaging And Labeling Full Stack Development, Experience working in an Agile development methodology; experience with RAG and LLM, We are seeking a skillful AI Engineer with Master's degree in Computer science or AI or relevant field for development of advanced AI/ML systems, including structured analytics, retrieval-augmented generation (RAG), agentic workflows, classification systems, and LLM-powered applications., * Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
-
Strong hands-on experience in Agentic AI frameworks and RAG architectures, including Graph RAG.
-
Proficiency Python and deep learning frameworks (e.g., PyTorch), with experience building and deploying LLM-powered systems.
-
Experience with LLM orchestration frameworks such as LangChain, LangGraph, and LlamaIndex.
-
Solid understanding of LLM inference, prompt engineering, and context management for enterprise-scale applications.
-
Working knowledge of AI safety and alignment techniques, including Guardrails, RLHF, and CLHF.
-
Experience designing and retrieval systems, embeddings, vector databases, and semantic search.
-
Familiarity with model evaluation, benchmarking, and human-in-the-loop feedback workflows.
-
Proficiency with development and collaboration tools (GitHub, VS Code, JIRA) and CI/CD practices.
-
Strong analytical and problem-solving skills with the ability to debug complex AI system behaviors (e.g., hallucinations, retrieval failures, routing issues).
-
Design, build, and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise AI applications.
-
Develop agentic workflows that integrate LLMs with tools, APIs, and structured/unstructured data sources.
-
Implement components across the RAG stack, including:
-
Document ingestion, chunking, and embedding strategies
-
Vector database integration and retrieval optimization, Artificial intelligence, Pyspark, Python, PySpark VS Code Metadata Chunking Debugging LangChain AI Safety Semantics Langgraph Operations Leadership Management LlamaIndex Agentic AI Scalability Benchmarking Tool Calling Deep Learning Hallucinations Problem Solving Network Routing Semantic Search Vector Database Computer Science Machine Learning Agile Methodology Unstructured Data Business Valuation Course Evaluations Prompt Engineering Workflow Management Information Retrieval Packaging And Labeling Full Stack Development
Benefits & conditions
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
- Medical, dental & vision
- Critical Illness, Accident, and Hospital
- 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available
- Life Insurance (Voluntary Life & AD&D for the employee and dependents)
- Short and long-term disability
- Health Spending Account (HSA)
- Transportation benefits
- Employee Assistance Program
- Time Off/Leave (PTO, Vacation or Sick Leave) Workplace Type