Job type
- Full-time
Job description
Job Title: AI Engineer
Location: Richardson, TX (Onsite)
Duration: Months
Experience: + years overall, with + years in AI/ML development
Must-Have Skills:
- Python , 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 /, SQLAlchemy, Alembic, advanced SQL
- Docker and Linux
- Redis, Pydantic, Pandas, PyArrow
- ETL/ELT and Prefect
- OAuth , MSAL and enterprise API integrations
- Microsoft Graph API — SharePoint, Outlook, Planner, OneDrive
- ServiceNow REST API and Splunk SDK
AI / LLM / RAG:
- 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 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 Responsibilities
- RAG & LLM Engineering — Build RAG solutions, agent workflows, prompt grounding and LLM fine-tuning.
- Enterprise API Integrations — Develop OAuth integrations with Microsoft Graph, SharePoint, Outlook, Planner, OneDrive, ServiceNow and Splunk.
- Vector Search — Design and optimize Qdrant/Milvus-based vector databases, embeddings, retrieval, filtering and reranking.