AI/ML Engineer

Job Title: AI/ML Engineeer | Telecom | C2C
Work Location & Reporting Address: Richardson, TX 75082 (Onsite-Hybrid. Candidates willing to relocate to client location will be considered)
Contract duration: 12
 

Must Have Skills:
⦁ Python 3.11+
⦁ LangGraph
⦁ LangChain
⦁ Azure OpenAI/OpenAI APIs
⦁ FastAPI
⦁ Vector Databases
⦁ PostgreSQL
⦁ Docker

Nice to Have Skills:
⦁ Columnar performance tuning
⦁ Network operations domain knowledge
⦁ OAuth 2.0
⦁ Microsoft Graph API

Detailed Job Description:
Overall 8+ years’ experience with 5+ years in AI development. PFB the technology skills required.

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