AI Engineer, Senior

Job not on LinkedIn

🔥 4 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Logiciel Solutions | AI-Powered Teams That Feel In-House

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2011

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

Logiciel Solutions is an AI-first software engineering firm that embeds high-performing, AI-enabled development teams into client workflows to deliver web and mobile applications, AI agents, and cloud-native systems. They provide services including agentic/autonomous AI and AI agents for product and engineering workflows, MVP and SaaS development, UX/UI design, QA and test automation, data engineering for AI-readiness, and cloud engineering/DevOps (AWS). Logiciel targets tech leaders and product teams across sectors such as Real Estate/PropTech, Healthcare, FinTech/Financial Products, Martech, Construction, and Home Improvement, offering delivery-ready teams, AI-native architecture guidance, and extensive playbooks and whitepapers for engineering and AI adoption.

📋 Description

• Design and implement multi-step AI agents, reasoning flows, and automation workflows interacting with internal and external systems. • Implement agent logic, tooling, and workflow orchestration. • Develop retrieval pipelines and knowledge-grounding workflows. • Build structured extraction flows using LLMs and transformation logic. • Convert prototypes into production-ready services with monitoring and predictable behavior. • Ensure agents are explainable, observable, and have defined failure and fallback paths. • Define architectures for applied AI solutions using TypeScript/Node or Python. • Integrate agents with APIs, databases, event systems, and existing product surfaces, including protocols such as MCP or A2A. • Establish patterns for prompt management, model selection, retrieval, and verification. • Implement evaluation pipelines to monitor accuracy, drift, and reliability. • Build reusable modules and internal tooling to accelerate future AI development. • Build functional prototypes and demos to validate ideas. • Assess feasibility, complexity, and risks of proposed AI features. • Collaborate with sales and delivery teams on scope and technical approach. • Advise on trade-offs between model and architecture choices. • Help create realistic timelines and delivery plans. • Mentor backend engineers on AI patterns, workflows, and integration techniques. • Introduce practices for testing, evaluation, observability, and versioning. • Share knowledge on prompting, model behavior, and tool usage. • Establish standards for applied AI solution design and delivery.

🎯 Requirements

• 5+ years of experience stated in the experience range. • 6–15 years of software engineering experience with strong backend fundamentals. • Proven experience building and shipping applied AI systems or agents in production. • Strong hands-on experience with TypeScript/Node and Python. • Experience with agent frameworks or custom orchestration patterns. • Strong understanding of retrieval workflows, embeddings, chunking, and evaluation methods. • Experience working with vector databases and related tooling. • Decent understanding of underlying infrastructure and production operations, including LLMOps. • Ability to design and integrate multi-step workflows with external systems and APIs. • Comfortable working from prototype to production with attention to reliability and observability. • Ability to break down ambiguous ideas and propose clear, technically grounded solutions. • Strong communication skills, especially when explaining feasibility and technical trade-offs. • Nice to have: experience with speech-to-text or text-to-speech pipelines. • Nice to have: familiarity with workflow engines or orchestration tools. • Nice to have: experience with evaluation frameworks or custom benchmarking pipelines. • Nice to have: exposure to model monitoring, versioning, or lightweight MLOps practices. • Nice to have: prior involvement in pre-sales or client-facing technical discussions. • Nice to have: experience mentoring engineers on applied AI practices. • Nice to have: experience with no-code tools like n8n.

🏖️ Benefits

• Become the foundational hire for Applied AI at Logiciel. • Own high-impact projects from design to deployment. • Influence architecture, patterns, and future team growth. • Work in a culture that values engineering clarity, autonomy, and tangible results.