IT - Technology Specialist - IT Service, Support and Operations | Telecom | OSS/BSS

POC: Sam ChavezATTENTION ALL SUPPLIERS!!!READ BEFORE SUBMITTING: UPDATED CONTACT NUMBER and EMAIL ID is a MANDATORY REQUEST from our client for all the submissions We prioritize endorsing those with complete and accurate information Avoid submitting duplicate profiles. We will Reject/Disqualify immediately. Make sure that candidate's interview schedules are updated. Please inform the candidate to keep their lines open. Please submit profiles within the max proposed rate. Please make sure to TAG the profiles correctly if the candidate has WORKED FOR INFOSYS as a SUBCON or FTE.MANDATORY: Please include in the resume the candidate s complete & updated contact information (Phone number, Email address and Skype ID) as well as a set of 5 interview timeslots over a 72-hour period after submitting the profile when the hiring managers could potentially reach to them. PROFILES WITHOUT THE REQUIRED DETAILS and TIME SLOTS will be REJECTED.Job Title: Technology Specialist - IT Service, Support and Operations | Telecom | OSS/BSSWork Location & Reporting Address: Richardson, TX 75082 (Onsite-Hybrid. Candidates willing to relocate to client location will be considered)Contract duration: 12MAX VENDOR RATE: $80 to $85 per hour maxTarget Start Date: 15 Sep 2026Does this position require Visa independent candidates only? YesMust 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 APIDetailed 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) aio / (async 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 consumptionRetrieval, 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: 1. Faithfulness 2. Relevance 3. NDCG4. MRR Trace-level RAG evaluation (Langfuse) Data Engineering & ETL Prefect 2.x / 3.x 1. Flows, tasks, futures2. Deployments (YAML)3. Scheduling ETL/ELT design o Schema evolution1. Query optimization OAuth authentication Warehouse/schema management PostgreSQL 16/17 1. psycopg 3.x 2. Connection pooling 3. SQLAlchemy 2.x (ORM + asyncio) 4. Alembic migrations 5. Advanced SQL 6. Multi-table JOINs 7. CTEs 8. Window functions Timezone conversion Pandas 2.x (complex multi-stage transformations) PyArrow / columnar formats Azure Blob Storage (azure-storage-blob) Document ingestion/parsing: 1. Docling2. Unstructured3. python-docx4. python-pptx DevOps & Platform Docker Linux fundamentalsNice-to-Haves Ray (distributed execution) Columnar performance tuning Network operations domain knowledge NOC / alarm correlation familiarityAPI & 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 mgmt Bulk operations Splunk SDK Saved searches Async queries Log analysis Azure AD app registrations IPAM / OTNA integrations (nice-to-have domain exposure) Minimum Years of Experience: 7+ yearsCertifications Needed: NoneTop 3 responsibilities you would expect the Subcon to shoulder and execute: RAG prompt grounding strategies LLM finetuning API Enterprise Integrations OAuth 2.0 client credentials flow, token lifecycle MSAL browser service principal flows Microsoft Graph API SharePoint Outlook Planner OneDrive Vector databases Qdrant andor MilvusInterview Process (Is face to face required?) 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Project Code: Project code for Network Apps AI develop