位于大连市的 11 个优质system engineer职位（正在招聘！）

AI Native Software Engineering Asso. Manager
Accenture —大连市
- 全职
14天
Customer Engineer-DDP/MDP/CMP/ETCH
Applied Materials —大连市
- 全职
Coating Engineer 涂装工程师
Atlas Copco Group —大连市
Test Automation Engineer (In-Vehicle Infotainment)
Luxoft —大连市
Application Engineer 技术支持
Atlas Copco Group —大连市
Engineering Supervisor
Burgmann Dalian Co. Ltd. —大连市
Customer Support Engineer - DL
ASML —大连市
Software Developer - Early Career
Ericsson —大连市
QA (Quality Assurance) Manager
Veeva Systems —大连市
Field Process Engineer
Lam Research —大连市
Director After Sales
Atlas Copco Group —大连市

More jobs to discover

Find similar jobs that you might be interested in.

Customer Engineer-DDP/MDP/CMP/ETCH
Applied Materials —大连市
Install, maintain, and upgrade customer equipment. Collaborate with Senior Field Service Engineers [Customer Engineers] and/or the customer to understand…

我想收到关于大连市的 system engineer 的最新职位提醒

一旦登录您的账户，即表明您同意 SimplyHired 的服务条款和我们的Cookie 协议及隐私政策。

查看更多地区的职位

system engineer jobs near 大连市

位于陕西省的Software Engineer职位

位于上海市闵行区的Software Engineer职位

位于天津市西青区的Software职位

位于上海市南汇区的Software Engineer职位

位于上海市的Software Engineer职位

位于上海市的Package Development Engineer职位

位于浙江省的Process Engineer职位

位于北京市的Data Center Engineer职位

位于北京市的Cloud Engineer职位

位于广东省的Equipment Engineer职位

位于成都市的Design Engineer职位

位于张家港市的Process Engineer职位

位于昆山市的Process Engineer职位

位于中山市的Process Engineer职位

位于常州市的Process Engineer职位

位于深圳市南山区的Sales Director职位

位于成都市双流县的Sales Director职位

位于杭州市的Sales Director职位

位于深圳市的Sales Representative职位

位于上海市的Plan Manager职位

AI Native Software Engineering Asso. Manager

Accenture -
大连市

立即申请

职位详情

全职
14 天前

完整职位描述

Role Description
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.

As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.

This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.

Key Responsibilities

Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability
Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets
Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management
Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring
Embed directly with client engineering teams to design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs
Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster
Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms

Basic Qualifications

5+ years of software engineering experience in production environments
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable
Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level
Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs
RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering
LLMOps fundamentals: eval harness design, prompt versioning, and production observability
Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)
Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience
Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure

立即申请

完善您的搜索

在大连市的system engineer个职位

AI Native Software Engineering Asso. Manager

Customer Engineer-DDP/MDP/CMP/ETCH

Coating Engineer 涂装工程师

Test Automation Engineer (In-Vehicle Infotainment)

Application Engineer 技术支持

Engineering Supervisor

Customer Support Engineer - DL

Software Developer - Early Career

QA (Quality Assurance) Manager

Field Process Engineer

Director After Sales

More jobs to discover

我想收到关于大连市的 system engineer 的最新职位提醒

查看更多地区的职位

求职者工具

雇主工具

浏览

保持联系

完善您的搜索

在大连市的system engineer个职位

More jobs to discover

我想收到关于 大连市 的 system engineer 的最新职位提醒

查看更多地区的职位

我想收到关于大连市的 system engineer 的最新职位提醒