AI ENGINEER

About the role

We are looking for a candidate with overall 8+ years’ experience, including 5+ years in AI development. This role is open to candidates across the US, with the option to work from any DC office.

Skills

Core Language & Architecture

• Python 3.11+
• Advanced type hints (PEP 484), static typing discipline
• Async programming (asyncio, async/await, async generators)
• aiohttp / httpx (async HTTP clients)
• Pydantic v2 (BaseModel, validation, settings management)
• Structured logging & tracing patterns
• Redis (pub/sub, TTL, async clients)
• REST API design & integration patterns
• Retry/backoff strategies (Tenacity)
• Concurrency patterns (parallel tool calls, task orchestration)

AI / LLM / Agent Systems

• LangGraph (state machines, conditional edges, checkpointing)
• LangChain 0.3.x (LLMChain, StructuredTool, retrievers, prompt templates)
• ReAct-style agent architectures
• Tool-based agent design (40+ tool environments)
• Azure OpenAI / OpenAI APIs (GPT-4o, deployment mgmt, rate limits, token budgeting)
• Prompt engineering (few-shot, structured output, JSON mode)
• PydanticOutputParser / structured LLM responses
• Guardrails / PII redaction patterns
• Memory abstractions for agents
• Langfuse (trace instrumentation, evaluation, prompt management)
• LLM fallback chains & error recovery
• RAG prompt grounding strategies
• LLM fine-tuning
• Neural Network training & tuning
• Traditional ML models (random forest, k-means clustering, linear regression, etc.)
• MCP development and consumption

Retrieval, Search & RAG Engineering

• Vector databases (Qdrant and/or Milvus)
• HNSW indexing parameters
• Filtering strategies
• Embedding pipelines (OpenAI ada-002 or equivalent)
• Batch embedding & re-indexing workflows
• Hybrid retrieval (BM25 + semantic)
• Score fusion strategies
• Cross-encoder reranking (BAAI/bge models)
• FastAPI-based inference services
• LangChain retriever abstractions
• RAG evaluation metrics: Faithfulness, Relevance, NDCG, MRR
• Trace-level RAG evaluation (Langfuse)

Data Engineering & ETL

• Prefect 2.x / 3.x (Flows, tasks, futures, Deployments (YAML), Scheduling)
• ETL/ELT design
• Schema evolution
• Query optimization
• OAuth authentication
• Warehouse/schema management
• PostgreSQL 16/17
• psycopg 3.x (Connection pooling)
• SQLAlchemy 2.x (ORM + asyncio)
• Alembic migrations
• Advanced SQL (Multi-table JOINs, CTEs, Window functions, Timezone conversion)
• Pandas 2.x (complex multi-stage transformations)
• PyArrow / columnar formats
• Azure Blob Storage (azure-storage-blob)
• Document ingestion/parsing: Docling, Unstructured, python-docx, python-pptx

DevOps & Platform

• Docker
• Linux fundamentals

Nice-to-Haves

• Ray (distributed execution)
• Columnar performance tuning
• Network operations domain knowledge
• NOC / alarm correlation familiarity

API & Enterprise Integrations

• OAuth 2.0 (client credentials flow, token lifecycle)
• MSAL (browser + service principal flows)
• Microsoft Graph API
• SharePoint, Outlook, Planner, OneDrive
• Pagination
• App permissions
• ServiceNow REST API, Table API
• Incident/change management
• Bulk operations
• Splunk SDK (Saved searches, Async queries, Log analysis)
• Azure AD app registrations
• IPAM / OTNA integrations (nice-to-have domain exposure)