Forward Deployed Engineer, Agentic AI
转型 AI 开发人员，代理 AI 关于角色的重组正在为客户设计，部署和优化代理 AI 解决方案建立专用的能力。我们寻找一个前进部署工程师：技术，面向客户的构建者可以将人工智能的能力转换成在客户环境中工作生产系统。这个职位融合了嵌入式，实践中的交付模式与更广泛的技术咨询工作 Redapt 客户需要从人工智能投资中获得真正的 ROI.你会写 Python 产品代码，坐在客户面前以简单语言解释技术交易，帮助客户和内部 Redapt 团队从他们现有的人工智能工作负载中获取更多价值。这一角色是故意比典型的 FDE 职位更广泛，将嵌入式交付与技术咨询工作元素结合起来，如代币和模型优化，人工智能安全和劳动负载 ROI,支持长期客户成功。你会做什么嵌入式传输 &工程 ·直接与客户团队进行设计，构建和运输基于克洛德模型的生产应用程序和集成。·编写并维护人工智能集成，代理工作流和内部工具的生产质量 Python 代码。· 设置和配置代理链 （包括 Azure Foundry,AWS Bedrock,Claude Cowork 式部署）以使客户团队能够将 AI 用于实际业务流程。· 从客户参与度中编码可重复的部署模式并将其传递给更广泛的团队，以便未来的参与率更快地移动。客户咨询与利益相关者参与度 · 将发现，架构选项和建议直接向客户利益相关方提供，为技术和非技术受众翻译技术概念。· 在对象的整个过程中建立持久，有信任的关系。· 与内部团队合作评估现有 AI 工作负载，并确定改善 ROI 的机会，无论是通过更好的架构，工具或工作流程重新设计。模型优化和人工智能安全 · 咨询客户和内部 Redapt 团队关于 टोकन优化和模型选择来控制成本和提高性能。· 评估和调整模型配置和提示策略以提高输出质量和可靠性给定的工作负载。·识别人工智能的安全考虑 （数据处理，访问控制，快速注射，模式治理）并将这些构成部署建议。
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Forward Deployed Engineer, Agentic AI
About the Role
Redapt is building dedicated capacity to design, deploy, and optimize agentic AI solutions for clients. We are looking for a Forward Deployed Engineer: a technical, client-facing builder who can turn AI capabilities into working production systems inside customer environments.
This role blends an embedded, hands-on delivery model with the broader technical advisory work Redapt clients need to get real ROI from AI investments. You will write production Python code, sit in front of clients to explain technical tradeoffs in plain language, and help both customers and internal Redapt teams get more value out of their existing AI workloads. This role is intentionally broader than a typical FDE position, combining embedded delivery with elements of technical advisory work, such as token and model optimization, AI security, and workload ROI, that support long-term client success.
What You'll Do
Embedded Delivery & Engineering
- Embed directly with client teams to design, build, and ship production applications and integrations built on Claude models.
- Write and maintain production-quality Python code for AI integrations, agent workflows, and internal tooling.
- Set up and configure agentic harnesses (including Azure Foundry, AWS Bedrock, Claude Cowork-style deployments) so client teams can put AI to work on real business processes.
- Codify repeatable deployment patterns from client engagements and feed them back to the broader team so future engagements move faster.
Client Advisory & Stakeholder Engagement
- Present findings, architecture options, and recommendations directly to client stakeholders, translating technical concepts for both technical and non-technical audiences.
- Build durable, trusted relationships with client technical and business stakeholders over the life of an engagement.
- Work with internal teams to assess existing AI workloads and identify opportunities to improve ROI, whether through better architecture, tooling, or workflow redesign.
Model Optimization & AI Security
- Advise clients and internal Redapt teams on token optimization and model selection to control cost and improve performance.
- Evaluate and tune model configuration and prompting strategy to improve output quality and reliability for a given workload.
- Identify AI security considerations (data handling, access control, prompt injection, model governance) and build these into deployment recommendations.
Required Qualifications
- 3+ years in a technical, client-facing role such as forward deployed engineering, solutions engineering, or consulting with a software engineering background.
- Strong Python skills, with experience shipping production code, not just prototypes or notebooks.
- Hands-on production experience with LLMs, including:
- Agent development
- Evaluation
- Deployment at scale
- Demonstrated ability to communicate clearly and credibly with clients, including in live, in-person settings.
- Working knowledge of Azure Foundry, AWS Bedrock, OpenAI/Codex and the Anthropic/Claude platform (Claude API, tool use, Claude Code, or similar).
- Comfort operating with ambiguity and owning a technical engagement end-to-end.
Preferred Qualifications
- Experience with evaluation frameworks, RAG pipelines, or agent orchestration frameworks (e.g., LangGraph, LangChain, CrewAI).
- Familiarity with AI security, privacy, and governance considerations in enterprise environments.
- Experience with MLOps/LLMOps practices, including model monitoring and prompt management.
- Prior experience specifically with Azure Foundry, AWS Bedrock, or Anthropic's Claude platform (Claude for Enterprise, Claude Code, MCP).
- Background in enterprise IT systems or AI deployment patterns.
What Makes You Successful
- You can translate deep technical work into plain language that lands with engineers and executives alike.
- You thrive working embedded inside client environments and take ownership of outcomes, not just recommendations.
- You are comfortable operating across the full arc of an engagement, from writing production code to advising on cost, security, and architecture.
- You enjoy turning one-off engagement learnings into repeatable patterns so the next client moves faster.
Technologies & Methodologies
- Python
- OpenAI / Codex
- Anthropic / Claude API
- Agentic AI & Agent Development
- Azure AI Foundry
- AWS Bedrock
- AI Security & Governance
- RAG Pipelines (Preferred)
- LangGraph / LangChain / CrewAI (Preferred)
- MLOps / LLMOps (Preferred)
- MCP (Model Context Protocol) (Preferred)
Travel required:
· Travel typically 5% or less a year
Equal Employment Opportunity:
Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need.
Originally posted on Himalayas