Generative AI Engineer

L-com Global Connectivity

Generative AI Engineer building production-grade AI systems for a leading tech company. Focus on architecture, deployment, and operational improvement.

Posted 4/17/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $147,000 - $170,000 per yearWebsite

Tech Stack

Tools & technologies

AzureCloudDistributed SystemsDockerERPMicroservicesPySparkPythonVault

About the role

Key responsibilities & impact

Design and build production-grade generative AI systems - agentic workflows, multi-step RAG pipelines, and LLM-powered applications integrated with enterprise data and services
Define and implement reusable engineering patterns for prompt management, workflow versioning, structured outputs, tool orchestration, and rollback across production AI services
Apply judgment around model selection and routing, token and latency optimization, cost management, and the appropriate boundaries between AI-driven and deterministic application logic
Continuously evaluate emerging AI models, tools, and architectural approaches, incorporating improvements into existing systems incrementally
Integrate AI systems with enterprise data sources, internal APIs, and platforms to enable reliable, production-ready workflows
Own operational outcomes for production AI systems - reliability, latency, throughput, cost efficiency, and scalability targets
Implement and maintain monitoring, observability, tracing, and alerting frameworks to ensure operational visibility and rapid issue resolution
Design and maintain CI/CD pipelines for deployment, versioning, and release management of AI services
Lead production incident response and root cause analysis, driving systemic improvements that reduce recurrence
Build and maintain automated evaluation pipelines for LLM outputs - prompt regression testing, retrieval quality validation, and failure mode tracking
Implement human-in-the-loop controls, content guardrails, schema validation, and structured output enforcement to ensure trusted and auditable AI outputs
Secure AI systems against prompt injection, data leakage, and unauthorized access, aligning with enterprise compliance and security standards
Own the team's GenAI technical direction - defining and enforcing engineering standards, patterns, and best practices across all GenAI workstreams
Make and defend architectural decisions with clarity, providing the technical rationale needed for the Manager and stakeholders to align and move forward confidently
Work closely with the Manager, GenAI Engineering to receive, refine, and execute on scoped GenAI work - contributing technical judgment to prioritization and tradeoff decisions
Provide hands-on code review and technical guidance to engineers contributing to GenAI workstreams, raising overall quality through direct feedback and demonstration
Champion an iterative delivery culture - shipping incrementally, incorporating feedback, and improving continuously in a regular production release cadence

Requirements

What you’ll need

Demonstrated experience shipping production-grade LLM or generative AI systems - prompt and workflow design tradeoffs, model selection and routing decisions, tool use and agent orchestration boundaries, and the distinction between AI guardrails and deterministic application logic
Experience building automated evaluation pipelines for LLM outputs, including gold set construction, model-based evaluation approaches, prompt regression testing, retrieval quality validation, and failure mode analysis across the full LLM application stack
Experience implementing human-in-the-loop controls, content guardrails, and schema-based output validation for enterprise AI deployments
Strong track record designing, building, and operating complex distributed systems in enterprise production environments, with clear ownership of reliability, performance, and operational outcomes
Experience with CI/CD pipeline design and operation for AI services - including deployment strategies, versioning, and release management in production environments
Proven ability to define and enforce GenAI engineering standards, patterns, and best practices across a cross-functional team
Experience designing and operating cloud-native APIs, microservices, and event-driven architectures on Azure or equivalent cloud platform
Experience integrating AI systems with enterprise data sources, internal APIs, and security controls in compliance-sensitive environments
Demonstrated track record of shipping production AI systems iteratively - with regular release cadence, feedback incorporation, and continuous improvement
Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience
Experience designing and operating agentic AI systems and multi-step RAG architectures in production - retrieval quality optimization, chunking strategies, grounding, and ranking tradeoffs
Hands-on experience with Azure OpenAI, AI Foundry, App Service, Functions, Service Bus, Blob Storage, Key Vault, and Application Insights; familiarity with Bicep for IaC
Experience with Python frameworks commonly used in production AI services, including FastAPI, asyncio, and Pydantic
Familiarity with PySpark notebooks for data pipeline development
Experience deploying and managing containerized AI workloads using Docker or similar technologies
Familiarity with responsible AI principles, AI governance frameworks, and regulatory considerations relevant to enterprise AI systems
Familiarity with Bronze/Silver/Gold medallion architecture and staged data quality patterns for enterprise data pipelines
Domain experience in product data, PIM, ERP, master data management, data governance, ecommerce, or analytics platforms
Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account L-com Global Connectivity Website LinkedIn All Job Openings 201 - 500 employees Founded 1982 🔧 Hardware 📡 Telecommunications 🛍️ eCommerce 💰 Private Equity Round on 2006-03 Hardware
Telecommunications
eCommerce L-com Global Connectivity is a leading provider of wired, wireless, and industrial connectivity products. They specialize in custom cable assemblies and offer a wide range of connectivity solutions including adapters, antennas, and enclosures. With a commitment to fast delivery and high-quality products, L-com serves various industries including telecommunications, industrial automation, and healthcare. Generative AI Engineer Job not on LinkedIn 🔥 2 hours ago 🇺🇸 United States – Remote 💵 $147k - $170k / year ⏰ Full Time 🟡 Mid-level 🟠 Senior 🗣️ LLM Engineer Azure Cloud Distributed Systems Docker ERP Microservices PySpark Python Vault Apply Now Find Hiring Managers Customize resume for this job Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Design and build production-grade generative AI systems - agentic workflows, multi-step RAG pipelines, and LLM-powered applications integrated with enterprise data and services
Define and implement reusable engineering patterns for prompt management, workflow versioning, structured outputs, tool orchestration, and rollback across production AI services
Apply judgment around model selection and routing, token and latency optimization, cost management, and the appropriate boundaries between AI-driven and deterministic application logic
Continuously evaluate emerging AI models, tools, and architectural approaches, incorporating improvements into existing systems incrementally
Integrate AI systems with enterprise data sources, internal APIs, and platforms to enable reliable, production-ready workflows
Own operational outcomes for production AI systems - reliability, latency, throughput, cost efficiency, and scalability targets
Implement and maintain monitoring, observability, tracing, and alerting frameworks to ensure operational visibility and rapid issue resolution
Design and maintain CI/CD pipelines for deployment, versioning, and release management of AI services
Lead production incident response and root cause analysis, driving systemic improvements that reduce recurrence
Build and maintain automated evaluation pipelines for LLM outputs - prompt regression testing, retrieval quality validation, and failure mode tracking
Implement human-in-the-loop controls, content guardrails, schema validation, and structured output enforcement to ensure trusted and auditable AI outputs
Secure AI systems against prompt injection, data leakage, and unauthorized access, aligning with enterprise compliance and security standards
Own the team's GenAI technical direction - defining and enforcing engineering standards, patterns, and best practices across all GenAI workstreams
Make and defend architectural decisions with clarity, providing the technical rationale needed for the Manager and stakeholders to align and move forward confidently
Work closely with the Manager, GenAI Engineering to receive, refine, and execute on scoped GenAI work - contributing technical judgment to prioritization and tradeoff decisions
Provide hands-on code review and technical guidance to engineers contributing to GenAI workstreams, raising overall quality through direct feedback and demonstration
Champion an iterative delivery culture - shipping incrementally, incorporating feedback, and improving continuously in a regular production release cadence 🎯 Requirements
Demonstrated experience shipping production-grade LLM or generative AI systems - prompt and workflow design tradeoffs, model selection and routing decisions, tool use and agent orchestration boundaries, and the distinction between AI guardrails and deterministic application logic
Experience building automated evaluation pipelines for LLM outputs, including gold set construction, model-based evaluation approaches, prompt regression testing, retrieval quality validation, and failure mode analysis across the full LLM application stack
Experience implementing human-in-the-loop controls, content guardrails, and schema-based output validation for enterprise AI deployments
Strong track record designing, building, and operating complex distributed systems in enterprise production environments, with clear ownership of reliability, performance, and operational outcomes
Experience with CI/CD pipeline design and operation for AI services - including deployment strategies, versioning, and release management in production environments
Proven ability to define and enforce GenAI engineering standards, patterns, and best practices across a cross-functional team
Experience designing and operating cloud-native APIs, microservices, and event-driven architectures on Azure or equivalent cloud platform
Experience integrating AI systems with enterprise data sources, internal APIs, and security controls in compliance-sensitive environments
Demonstrated track record of shipping production AI systems iteratively - with regular release cadence, feedback incorporation, and continuous improvement
Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience
Experience designing and operating agentic AI systems and multi-step RAG architectures in production - retrieval quality optimization, chunking strategies, grounding, and ranking tradeoffs
Hands-on experience with Azure OpenAI, AI Foundry, App Service, Functions, Service Bus, Blob Storage, Key Vault, and Application Insights; familiarity with Bicep for IaC
Experience with Python frameworks commonly used in production AI services, including FastAPI, asyncio, and Pydantic
Familiarity with PySpark notebooks for data pipeline development
Experience deploying and managing containerized AI workloads using Docker or similar technologies
Familiarity with responsible AI principles, AI governance frameworks, and regulatory considerations relevant to enterprise AI systems
Familiarity with Bronze/Silver/Gold medallion architecture and staged data quality patterns for enterprise data pipelines
Domain experience in product data, PIM, ERP, master data management, data governance, ecommerce, or analytics platforms
Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Technical Project Manager, AI Infrastructure 🕒 6 days ago Vultr 201 - 500 🤖 Artificial Intelligence 🤝 B2B 🔧 Hardware Website LinkedIn All Job Openings Technical Project Manager ensuring efficient execution of engineering projects supporting AI infrastructure at Vultr. Collaborating with engineering teams to achieve project goals in a remote setting. 🇺🇸 United States – Remote 💵 $75k - $95k / year 🔥 Funding within the last year 💰 $329M Debt Financing - Vultr on 2025-06 ⏰ Full Time 🟢 Junior 🟡 Mid-level 🗣️ LLM Engineer 🚫👨‍🎓 No degree required Senior Machine Learning Engineer, LLM Engineer 🕒 April 8 Blue Orange Digital 51 - 200 🤖 Artificial Intelligence 🤝 B2B 🏢 Enterprise Website LinkedIn All Job Openings Expert-level Machine Learning Engineer leading LLM Engineering and Agentic AI solutions for Blue Orange Digital’s clients. Requires extensive ML/AI, data science experience focusing on cloud-native solutions. 🇺🇸 United States – Remote 💵 $9.5k / month 💰 $700k Corporate round on 2022-05 ⏰ Full Time 🟠 Senior 🗣️ LLM Engineer AWS Azure Cloud Google Cloud Platform Python SQL Lead Generative AI Engineer 🕒 April 2 CACI International Inc 10,000+ employees 🔒 Cybersecurity Website LinkedIn All Job Openings Lead Generative AI Engineer developing advanced AI solutions for CACI's federal programs. Responsible for technical architecture and mentorship while ensuring sustainable AI practices. 🇺🇸 United States – Remote 💵 $114.6k - $252.1k / year ⏰ Full Time 🟠 Senior 🗣️ LLM Engineer AWS Azure Cloud Google Cloud Platform JavaScript Python Senior Generative AI Engineer 🕒 April 1 Natera 1001 - 5000 🧬 Biotechnology ⚕️ Healthcare Insurance 💊 Pharmaceuticals Website LinkedIn All Job Openings Senior Generative AI Engineer responsible for designing and deploying AI/ML solutions to improve patient outcomes at Natera. Collaborating with cross-functional teams to enhance internal workflows. 🇺🇸 United States – Remote 💵 $125k - $156.3k / year ⏰ Full Time 🟠 Senior 🗣️ LLM Engineer 🦅 H1B Visa Sponsor AWS Python PyTorch Senior Software Engineer – AI Infrastructure 🕒 March 27 Kraken Digital Asset Exchange 1001 - 5000 ₿ Crypto 💸 Finance 💳 Fintech Website LinkedIn All Job Openings Senior Software Engineer building the infrastructure for AI agent systems at Kraken. Focusing on high-scale production systems using Rust with a strong emphasis on performance and reliability. 🇺🇸 United States – Remote 💵 $110.4k - $220.8k / year ⏰ Full Time 🟠 Senior 🗣️ LLM Engineer Distributed Systems Rust View More LLM Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs

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Hard Skills & Tools

generative AI systemsLLM-powered applicationsautomated evaluation pipelinesCI/CD pipeline designcloud-native APIsPython frameworkscontainerized AI workloadsprompt regression testingdata validationmulti-step RAG architectures

Soft Skills

technical judgmentleadershipcommunicationiterative delivery cultureproblem-solvingcollaborationfeedback incorporationroot cause analysisdecision-makingoperational visibility

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Computer ScienceMaster's degree in Artificial IntelligenceMaster's degree in Machine Learning