AI Engineer

eTeam Inc
Richardson, TX, United States
6 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

LangGraph Framework Application Programming Interfaces (APIs) Artificial Intelligence Artificial Neural Networks Microsoft Azure Microsoft Online Services Microsoft Outlook Cloud Storage Concurrent Computing Information Engineering Extract Transform Load (ETL) Data Masking
+42 more
Linux DevOps Information Retrieval Python (Programming Language) PostgreSQL Log Analysis Machine Learning OAuth Performance Tuning Query Optimization Redis OpenAI Azure Active Directory Search Technologies Microsoft SharePoint SQLAlchemy Systems Integration Data Logging Data Processing Qdrant Computer Network Operations Sql Optimization Normalized Discounted Cumulative Gain ReactJS Retrieval-Augmented Generation Transfer Learning Large Language Models Prompt Engineering HNSW (Hierarchical Navigable Small World) Langfuse β€” LLM Observability and Analytics Platform Agentic-AI Fastapi Microsoft Onedrive Pandas Milvus Restful APIs Pagination Splunk Data Pipelines Api Management Docker Servicenow

Job description

  • Build and maintain LLM/AI agents using LangGraph and LangChain
  • ReAct and tool-based agent architectures
  • Azure OpenAI/OpenAI integration, prompt engineering and structured outputs
  • RAG pipelines, embeddings, hybrid search and reranking
  • Vector search using Qdrant/Milvus, including HNSW indexing and filtering
  • RAG evaluation using Faithfulness, Relevance, NDCG and MRR
  • LLM fine-tuning and neural network/ML model development
  • Guardrails, PII redaction, memory, fallback and error-recovery patterns
  • Langfuse for tracing, evaluation and prompt management

Data Engineering / ETL:

  • Design ETL/ELT pipelines using Prefect
  • PostgreSQL, advanced SQL, joins, CTEs and window functions
  • Pandas, PyArrow and columnar data processing
  • Azure Blob Storage
  • Document ingestion/parsing using Docling, Unstructured, python-docx and python-pptx
  • Schema evolution, query optimization and warehouse/schema management

API & Enterprise Integrations:

  • OAuth 2.0 client-credentials flow and token lifecycle
  • MSAL and Azure AD app registrations
  • Microsoft Graph API integrations with SharePoint, Outlook, Planner and OneDrive
  • ServiceNow REST/Table APIs, incident/change management and bulk operations
  • Splunk SDK, saved searches, async queries and log analysis
  • Pagination and application permissions

DevOps / Platform:

  • Docker and Linux fundamentals
  • Async/concurrent processing, retry/backoff and structured logging/tracing
  • Redis pub/sub and TTL
  • Nice to have: Ray/distributed execution

Nice-to-Have:

  • Columnar performance tuning
  • Network operations / NOC / alarm correlation knowledge
  • IPAM / OTNA integrations

Top 3 Responsibilities

  1. RAG & LLM Engineering Build RAG solutions, agent workflows, prompt grounding and LLM fine-tuning.
  2. Enterprise API Integrations Develop OAuth 2.0/MSAL integrations with Microsoft Graph, SharePoint, Outlook, Planner, OneDrive, ServiceNow and Splunk.
  3. Vector Search Design and optimize Qdrant/Milvus-based vector databases, embeddings, retrieval, filtering and reranking.

Requirements

Experience: 7 years overall, with 5 years in AI/ML development

Must-Have Skills:

  • Python 3.11, advanced type hints, async programming
  • LangGraph and LangChain
  • Azure OpenAI / OpenAI APIs
  • FastAPI, REST APIs
  • Vector Databases Qdrant and/or Milvus
  • RAG, prompt engineering, grounding, agent development
  • PostgreSQL 16/17, SQLAlchemy, Alembic, advanced SQL
  • Docker and Linux
  • Redis, Pydantic, Pandas, PyArrow
  • ETL/ELT and Prefect 2.x/3.x
  • OAuth 2.0, MSAL and enterprise API integrations
  • Microsoft Graph API SharePoint, Outlook, Planner, OneDrive
  • ServiceNow REST API and Splunk SDK

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