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AI/ML Software Engineering - Talent Pipeline

AI开发工程限定地区(需当地身份)
公司Fullsteam
薪资未公开
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

工作在一个公司里很有趣,人们真正相信自己正在做的事情!Fullsteam 是垂直软件和嵌入式支付技术的领先供应商,致力于帮助企业通过提供无经验来繁荣。拥有超过1,900名员工的动态和不断增长的团队,我们致力于推动创新并提供最好的软件和支付解决方案,使中小企业能够实现多个行业中的发展。我们的目标是帮助客户生长他们的业务并让客户快乐。加入我们成为一家重视增长,卓越性和客户成功的前进型公司的一部分。我们正在为公司未来的机会构建一个非凡的人工智能工程人才管道。虽然这不是即时开放,但我们预计将在整个一年内在这里招聘大量人员。作为更广泛的人工智能战略的一部分,我们正在大力投资生成 AI,代理系统和环境智能,以改变我们的产品建设方式,内部运营和服务客户。这些举措将推动扩大的产品能力,生产率增长,提高客户体验以及可测量的客户满意度 (NPS) 改善。如果你对塑造下一代智能系统感到兴奋,我们鼓励你申请和与我们联系未来的角色。主要责任 · 构建生产软件 设计并实现可扩展后端服务,API 和数据管道,以重点放在可靠性,性能和维护性 ·开发代理系统 创建自主代理人利用 LLM 来推理,使用工具,并编程复杂的多步骤工作流程 建筑师规模 设计处理实时人工智能推断,对话状态以及工具执行的系统 · 设计,开发和部署机器学习模型,推动产品特性,改善用户参与度并增强决策流程 · 跨功能合作 与产品,设计和工程团队合作确定要求并提供人工智能驱动的功能。· 保持工程卓越性 写清洁,经过检验的代码;进行彻底的代码审查;支持整个团队最佳实践 · 保持最新状态 评估新兴机构框架,模式和工具;原型创建解决实际问题的新方法技能 & 能力 S

查看英文原文

It's fun to work in a company where people truly BELIEVE in what they're doing!
Fullsteam is a leading provider of vertical software and embedded payments technology dedicated to helping businesses flourish by providing their customers with seamless experiences. With a dynamic and growing team of over 1,900 employees, we are committed to driving innovation and delivering best-in-class software and payment solutions that empower small and medium-sized businesses across numerous industries. Our purpose is to help our customers grow their businesses and delight their customers. Join us and be a part of a forward-thinking company that values growth, excellence, and the success of our clients.
We’re building a pipeline of exceptional AI Engineering talent for future opportunities within our organization. While this is not an immediate opening, we anticipate significant hiring in this space throughout the year.
As part of our broader AI strategy, we are investing heavily in Generative AI, Agentic Systems, and Ambient Intelligence to transform how we build products, operate internally, and serve our customers. These initiatives will drive expanded product capabilities, productivity gains, enhanced customer experiences, and measurable improvements in customer satisfaction (NPS).
If you're excited about shaping the next generation of intelligent systems, we encourage you to apply and connect with us for upcoming roles.
Primary Responsibilities

  • Build production software – Design and implement scalable backend services, APIs, and data pipelines with a focus on reliability, performance, and maintainability
  • Develop agentic systems – Create autonomous agents that leverage LLMs to reason, use tools, and orchestrate complex multi-step workflows
  • Architect for scale – Design systems that handle real-time AI inference, conversation state, and tool execution with proper error handling and recovery
  • Design, develop, and deploy machine learning models that drive product features, improve user engagement, and enhance decision-making processes
  • Collaborate cross-functionally – Partner with Product, Design, and Engineering teams to define requirements and deliver AI-powered features.
  • Maintain engineering excellence – Write clean, well-tested code; conduct thorough code reviews; champion best practices across the team
  • Stay current – Evaluate emerging agentic frameworks, patterns, and tools; prototype new approaches to solve real problems

Skills & Competencies

Software Engineering (Core)

  • Strong system design, API design, and distributed systems knowledge
  • Clean code practices and testable architecture
  • Experience with concurrency, async programming, and performance optimization
  • Database experience (relational + vector stores)
  • CI/CD, observability, and production operations

Agentic Systems

  • Agent architecture (planning, orchestration, memory, tool use)
  • LLM integration (prompting, function calling, context management)
  • RAG pipelines (embeddings, vector search, retrieval strategies)
  • Reliability patterns for non-deterministic systems

Machine Learning (ML)

  • Understanding of training, inference, evaluation, and model tradeoffs
  • Familiarity with embeddings and vector representations
  • Exposure to frameworks such as PyTorch, Hugging Face, or scikit-learn
  • Experience adapting or fine-tuning models is a plus
  • Knowledge of evaluation metrics (precision/recall, F1, perplexity)

Nice to Have

  • Experience with agent orchestration frameworks (e.g., LangGraph, AutoGen)
  • Background in vector databases and semantic search
  • Familiarity with AI safety and guardrail patterns
  • Experience mentoring engineers or leading initiatives

Typical Qualifications for Consideration

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 6+ years of software engineering experience
  • 2+ years building applications leveraging LLMs or agentic systems
  • Proficiency in Python and modern frameworks (FastAPI, async/await)
  • Experience with cloud platforms (AWS preferred: Lambda, Bedrock, OpenSearch)
  • Proven ability to ship and operate production systems
  • Strong problem-solving and communication skills

Additional Information

This is an evergreen requisition designed to build our talent network for upcoming AI Engineering roles. If your background aligns, a member of our team may reach out to you as opportunities arise that match your experience and interests.

Fullsteam supports an inclusive workplace that values diversity of thought, experience, and background. Fullsteam is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state, or local law.
Originally posted on Himalayas

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