Forward Deployed Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate closely with client teams to design, develop, and deploy production applications and integrations utilizing Claude models.

• Create and uphold production-quality Python code for AI integrations, agent workflows, and internal tools.

• Configure and set up agentic harnesses, which include Azure Foundry, AWS Bedrock, and Claude Cowork-style deployments.

• Document and optimize repeatable deployment patterns from client projects and share them with the broader team.

• Deliver findings, architectural options, and recommendations directly to client stakeholders.

• Simplify technical concepts for both technical and non-technical audiences.

• Establish trusted relationships with both technical and business stakeholders throughout client engagements.

• Evaluate current AI workloads and pinpoint opportunities to enhance ROI through architecture, tooling, or workflow redesign.

• Provide guidance on token optimization and model selection to manage costs and boost performance.

• Analyze and fine-tune model configurations and prompting strategies to enhance output quality and reliability.

• Recognize AI security concerns and integrate them into deployment recommendations.

⛳️ Requirements

• A minimum of 3 years in a technical, client-facing role such as forward-deployed engineering, solutions engineering, or consulting, with a background in software engineering.

• Proficient in Python, with experience delivering production code rather than just prototypes or notebooks.

• Practical experience with LLMs, including the development, evaluation, and large-scale deployment of agents.

• Proven ability to communicate effectively and credibly with clients, including in live, face-to-face meetings.

• Familiarity with Azure Foundry, AWS Bedrock, OpenAI/Codex, and the Anthropic/Claude platform.

• Comfortable navigating ambiguity and managing a technical engagement from start to finish.

• Preferred: experience with evaluation frameworks, RAG pipelines, or agent orchestration frameworks such as LangGraph, LangChain, and CrewAI.

• Preferred: understanding of AI security, privacy, and governance issues in enterprise settings.

• Preferred: experience with MLOps/LLMOps practices, including model monitoring and prompt management.

• Preferred: prior experience specifically with Azure Foundry, AWS Bedrock, or Anthropic's Claude platform.

• Preferred: background in enterprise IT systems or AI deployment patterns.

🏝️ Benefits

• Travel typically constitutes 5% or less of the annual workload.

• Commitment to equal opportunity employment and protections against discrimination.