Applied AI Engineer, AI Center of Excellence
What you’ll do & how you’ll make your mark .
We are looking for ahands on Applied AI Engineer who combines strong software engineering fundamentals with practical AI problem solving. You will help build production AI experiences across Network Solutions, including conversational agents, business and website creation, knowledge and FAQ agents, content experiences, domain discovery, and intelligent automation.
You will work with senior engineers, architects, and product partners to turn customer and product problems into reliable, secure, observable, andcost efficientAI systems. This is an applied engineering role focused on building, measuring, and continuously improving real AI products.
Who you are & what you’ll need to succeed
Translate product requirements into practical AI solutions using LLMs, RAG, tool calling, agents, deterministic workflows, or traditional software whereappropriate.
Build production AI services using Python,FastAPI, asynchronous workers, PostgreSQL, Redis, queues, model APIs, and external tools.
Implement reliable tool calling agents andmulti stepworkflows that interact with internal APIs, MCP tools, business systems, and knowledge sources.
Build event driven workflows using RabbitMQ, Kafka, Azure Service Bus, or equivalent platforms, including retries, dead letter handling, idempotency, and failure recovery.
Build and improve RAG systems covering ingestion, chunking, embeddings, hybrid retrieval, reranking, metadata filtering, context construction, and citations.
Integrate models from OpenAI, Anthropic, Google,xAI, and open weight ecosystems, and help select models based on quality, latency, reliability, and cost.
Build and run AI evaluations using curated datasets, regression tests, retrieval metrics, LLM as judge techniques,groundednesschecks, and tool execution evaluation.
Debug hallucinations, retrieval failures, incorrect tool usage, agent loops, latency issues, provider failures, and unexpected inference costs.
Operate as an AI powered engineer using Cursor, Claude Code, OpenAI Codex, or equivalent coding agents to accelerate implementation, testing, debugging, refactoring, and documentation.
What we’re looking for
3 or more years of professional software engineering experience building production backend, distributed, orcloud basedsystems.
At least 1 year ofhands onexperience building Applied AI, LLM, RAG, NLP, oragent basedapplications, with production experience strongly preferred.
Strong Python skills including
FastAPI, asynchronous programming,Pydantic,SQLAlchemyorSQLModel, andproductionAPI development.
Good backend and distributed systems fundamentals including REST APIs, concurrency, background processing, caching, reliability, and production debugging.
Hands on experience with RabbitMQ, Kafka, Azure Service Bus, or equivalent queue and messaging architectures isrequired.
Hands onexperience integrating LLM APIs and building structured output, function calling, tool calling, or agent execution workflows.
Experience building or contributing to a RAG or knowledge grounded system, including retrieval, embeddings, indexing, context construction, and evaluation.
Working knowledge of PostgreSQL and data modeling, with exposure to Redis,pgvector, vector databases, or hybrid search technologies.
Demonstrated use of AI coding agents such as Cursor, Claude Code, Codex, or equivalent tools as a regular part of software engineering work.
Nice to have.
You should be comfortable going beyond a working demo andunderstandthe core engineering patterns needed to make AI systems reliable in production.
Understanding ofprompting, structured outputs, tool schemas, context management, retries, fallbacks, rate limits, caching, and streaming…
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