Forward Deployed Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Forward Deployed Engineer based in United States. The Forward Deployed Engineer will design, build, and deploy advanced AI-powered solutions within complex enterprise environments. This role combines deep technical expertise with client-facing collaboration to help organizations operationalize next-generation AI capabilities. You will work closely with stakeholders, engineering teams, and business leaders to create scalable agentic platforms that solve real-world challenges. The position offers the opportunity to work on cutting-edge AI systems, including LLM-powered agents, automation workflows, and intelligent enterprise applications. You will contribute across architecture, implementation, deployment, and optimization while adapting solutions to diverse client needs. This is an impactful opportunity for an experienced engineer who enjoys solving complex problems, collaborating directly with customers, and driving innovation in a fast-moving environment. \n Accountabilities: The Forward Deployed Engineer will be responsible for delivering scalable AI solutions by combining software engineering expertise, architecture skills, and strong consulting capabilities. This role requires close collaboration with client teams to design, implement, and deploy intelligent systems that integrate effectively with existing technology ecosystems. Design, build, and deploy agentic platforms and AI-powered solutions within enterprise client environments. Develop scalable LLM-based applications using modern AI frameworks and engineering practices. Architect LLM orchestration workflows using technologies such as LangGraph, CrewAI, AutoGen, and related frameworks. Build and implement multi-agent systems supporting tool usage, workflow automation, memory, and decision-making capabilities. Design and deploy Retrieval-Augmented Generation (RAG) pipelines connected to enterprise data sources. Integrate AI platforms with client systems, including APIs, cloud services, data platforms, and enterprise applications. Create deployment architectures across cloud, on-premise, and hybrid environments. Configure and manage Kubernetes-based deployments to support reliable application delivery. Collaborate with technical and non-technical stakeholders to understand business needs and deliver effective solutions. Support complex client engagements by translating business challenges into practical technical outcomes. Adapt quickly to changing priorities while continuously improving solutions through direct user feedback. Requirements: The ideal candidate is a highly experienced software engineer with strong expertise in AI systems, distributed architectures, and enterprise technology delivery. They should combine technical depth with consulting skills and the ability to work effectively with diverse teams. Significant experience operating at a Senior Engineer level, typically with 8+ years of commercial engineering experience. Proven experience designing and building AI-powered platforms using Python and modern AI frameworks. Strong understanding of LLM architectures, agent-based systems, and AI application development. Experience implementing multi-agent workflows, orchestration patterns, and intelligent automation solutions. Hands-on experience building Retrieval-Augmented Generation (RAG) systems and integrating enterprise data sources. Experience integrating applications with APIs, cloud platforms, databases, and enterprise systems. Ability to design and deploy solutions using cloud, hybrid, and on-premise environments. Experience with Kubernetes configuration and workload deployment. Strong collaboration skills with both technical teams and business stakeholders. Consulting experience delivering complex projects and solving real business problems. Ability to thrive in dynamic environments with evolving requirements and direct customer interaction. Nice-to-have experience with Golang, React, and advanced Kubernetes implementations. Benefits: Competitive base salary range of $145,000 - $180,000 USD, plus annual bonus opportunities and benefits. Annual company bonus program tied to overall business performance. Fully remote and flexible working environment designed to support work-life balance. Flexible time off policy, including vacation days, public holidays, and additional leave options. Remote working allowance to support a comfortable and productive home workspace. Company-provided essential equipment for remote work. Professional development and training allowance to support continued learning and career growth. Private healthcare coverage. 401(k) plan with employer matching contributions up to 4%. Opportunity to work on innovative AI projects with enterprise clients and solve complex technical challenges. Regular collaboration with a global team of engineers, designers, and technology experts. Travel opportunities to client sites within the United States, with travel expenses covered. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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