Forward deployed engineer

Salt; United States; On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Remote work

Travel up to 20%

Performance bonus

Job summary

Salt is seeking a Senior Forward Deployed Engineer to bridge AI and enterprise realities. You will embed with client teams to architect, integrate, and launch LLM-powered agentic platforms, turning theory into scalable workflows.

Lead AI deployment, orchestration with AutoGen/CrewAI/LangGraph, and seamless integration with cloud or on‑prem ecosystems while applying strong client-facing communication.

Qualifications

• 8+ years of commercial software engineering experience.
• Proficiency in Python and modern AI frameworks.
• Experience deploying workloads with Kubernetes.
• Strong communication skills and client-facing delivery.

Responsibilities

• Architect and deploy multi-agent systems and RAG pipelines leveraging enterprise data.
• Orchestrate LLM workflows using AutoGen, CrewAI, LangGraph.
• Integrate AI platforms with cloud, APIs, and data platforms.
• Design deployment architectures across cloud, hybrid, or on‑premises; manage with Kubernetes.
• Collaborate with client stakeholders to translate business goals into technical roadmaps.

Skills

Python

AI frameworks

Kubernetes

Consultative mindset

Tools

AutoGen

CrewAI

LangGraph

Job description

Senior Forward Deployed Engineer (AI & Enterprise Solutions)

Location: Remote (East Coast preferred) | Up to 20% Client Travel

Compensation: base + 10% annual performance bonus

The Opportunity

We are looking for a client-facing engineer to bridge the gap between artificial intelligence and enterprise reality. In this role, you will act within our clients, embedding directly with their teams to architect, integrate, and launch sophisticated, LLM-powered agentic platforms. You will turn theoretical AI capabilities into scalable, production-ready workflows that solve real business problems.

What You'll Drive

• AI Architecture & Deployment: Architect and launch robust multi-agent systems and Retrieval-Augmented Generation (RAG) pipelines that securely leverage enterprise data sources.
• Orchestration: Leverage advanced frameworks like AutoGen, CrewAI, and LangGraph to manage complex LLM workflows, tool use, and memory.
• Seamless Integration: Connect bespoke AI platforms with existing corporate ecosystems, including cloud infrastructure, enterprise APIs, and data platforms.
• Infrastructure Management: Design versatile deployment architectures across cloud, hybrid, or on-premises environments, and manage workload deployments via Kubernetes.
• Strategic Consulting: Partner directly with both technical and non-technical client stakeholders to translate complex business objectives into actionable, iterative technical roadmaps.

What You Bring

• Senior-Level Expertise: A proven track record of complex software delivery, typically reflecting 8+ years of commercial engineering experience.
• Technical Stack: Deep proficiency in Python alongside modern AI frameworks.
• Infrastructure Chops: Solid foundational experience configuring and deploying workloads with Kubernetes.
• Consultative Mindset: Exceptional communication skills with a high comfort level iterating directly with end-users in fast-paced, dynamic environments.
• Bonus Points: Hands-on coding experience with Golang or React (frontend), as well as an advanced understanding of Kubernetes.