Remote Client-Facing AI Systems Engineer

Praxent; North Carolina; Remote; USD 156,000 - 186,000; Full time

Benefits offered by this job

Medical, dental, vision

IRA with match

15 days PTO + 9 US holidays + wellness

Parental leave

Remote work flexibility

Job summary

Praxent is seeking a Forward Deployed Engineer to embed with a client in the financial services space and build production AI systems that run in their environment. You will own end-to-end workstreams, from problem framing to production delivery, collaborating with client engineers and Praxent teams to ensure compliance and reliability.

The role emphasizes solving real-world constraints, integrating with legacy systems, and delivering robust, auditable AI solutions that can operate after

Qualifications

• 3+ years shipping production software that others depend on.
• Direct experience with LLM/agentic systems (RAG, agent frameworks, vector stores, evals) is ideal.
• Fluency in Python and/or TypeScript; comfortable across the stack and a major cloud; containers and CI/CD.
• Experience embedded within a client or customer environment with real-world data.
• Experience in banking, lending, or payments is strongly preferred, including working with risk/compliance partners.

Responsibilities

• Shipped, dependable AI in the client's environment with agentic features that meet functional and compliance requirements.
• Own a work stream from understanding the client's problem through to a delivered, documented solution.
• AI that fits their world with clean integration to legacy cores, governed data, and identity/infrastructure.
• Systems the client can run without you, including runbooks and handoffs for ongoing operation.
• Earned trust on the ground by clear communication and reliable follow-through.

Skills

Shipping production software

Python/TypeScript

Cloud platforms (AWS/Azure/GCP)

Containers & CI/CD

Client embedding experience

Risk & compliance in regulated env

Job description

Praxent is seeking a Forward Deployed Engineer to embed with a client in the financial services space and build production AI systems that run in their environment. You will own end-to-end workstreams, from problem framing to production delivery, collaborating with client engineers and Praxent teams to ensure compliance and reliability.

The role emphasizes solving real-world constraints, integrating with legacy systems, and delivering robust, auditable AI solutions that can operate after