Forward Deployed Engineer

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.
• Architect multi-agent systems with reliable tool use, memory, and orchestration patterns that perform accurately in high-stakes environments 
• 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
• Instrument and monitor agentic systems in production using observability tooling; iterate rapidly based on real user behavior and feedback

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.
• Partner with product managers and customer success to deeply understand user problems and translate them into elegant, production-grade AI solutions 
• 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.