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Remote Open Source Developer Jobs in Alabama (NOW HIRING)

... Remote (Open) Location Arizona - Home Teleworkers Additional Locations Alabama - Home Teleworkers ... Define criteria and controls for an authoritative data source (ADS) * Lead the design and ...

Job Title AI Strategy Lead - Remote Requisition Number R7687 AI Strategy Lead - Remote (Open ... Bachelor's degree in business, engineering, or related field. * 5-7 years of experience in ...

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Remote Open Source Developer information

What are the key skills and qualifications needed to thrive as a Remote Open Source Developer, and why are they important?

To thrive as a Remote Open Source Developer, you need strong programming skills (often in languages like Python, JavaScript, or C++), familiarity with open source workflows, and a solid understanding of version control systems like Git. Experience with collaborative platforms such as GitHub or GitLab, and familiarity with continuous integration (CI) tools, are typically expected. Excellent written communication, self-motivation, and the ability to work independently and asynchronously help you stand out in distributed teams. These skills and qualities are essential to effectively contribute code, engage with global communities, and maintain productivity in a remote, open-source environment.

How does a remote open source developer typically collaborate with distributed teams and community contributors?

As a remote open source developer, collaboration often takes place through online platforms such as GitHub, GitLab, and community forums. You will regularly participate in code reviews, contribute to discussions on issue trackers, and join virtual meetings or chat channels with both core team members and external contributors. Strong written communication skills are essential, as most interactions are asynchronous and require clear documentation. You'll also need to be proactive in seeking feedback and providing updates, ensuring smooth progress on projects across different time zones.

What is a Remote Open Source Developer?

A Remote Open Source Developer is a software engineer who contributes to open source projects while working from a location outside of a traditional office. These developers collaborate with distributed teams, often using online platforms like GitHub or GitLab to share code and track issues. Their work involves writing, testing, and documenting code, as well as reviewing contributions from others. Remote Open Source Developers may be volunteers or paid contributors, and they typically engage with a global community to improve and maintain open source software.
What are the most commonly searched types of Open Source Developer jobs in Alabama? The most popular types of Open Source Developer jobs in Alabama are:
What are popular job titles related to Remote Open Source Developer jobs in Alabama? For Remote Open Source Developer jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Remote Open Source Developer jobs in Alabama look for? The top searched job categories for Remote Open Source Developer jobs in Alabama are:
What cities in Alabama are hiring for Remote Open Source Developer jobs? Cities in Alabama with the most Remote Open Source Developer job openings:
Infographic showing various Remote Open Source Developer job openings in Alabama as of May 2026, with employment types broken down into 84% Full Time, and 16% Contract. Highlights an 100% Remote job distribution.
Senior MLOps & Generative AI Engineer - Remote

Senior MLOps & Generative AI Engineer - Remote

Sentara Healthcare

Centre, AL • On-site, Remote

$98.90K - $135.90K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Sentara Health rating

6.8

Company rating: 6.8 out of 10

Based on 379 frontline employees who took The Breakroom Quiz

488th of 864 rated healthcare providers


Job description

City/State
Virginia Beach, VA
Work Shift
First (Days)
Overview:
Sentara is hiring a Senior MLOps & Generative AI Engineer!
This position is fully remote!
Candidates must reside in one of the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming.
Overview
We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence.
This role combines two critical focus areas:
  • MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities.
  • Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks.

As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments.
Key Responsibilities
MLOps Engineering Responsibilities
  • Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management.
  • Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments.
  • Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation.
  • Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads.
  • Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability.
  • Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes.
  • Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment.
  • Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code.
  • Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them.
  • Support enterprise AI governance, compliance, auditability, and model risk management requirements.
  • Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems.

Generative AI Engineering Responsibilities
  • Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies.
  • Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
  • Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability.
  • Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases.
  • Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics.
  • Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments.
  • Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications.
  • Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments.
  • Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows.
  • Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement.
  • Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives.
  • Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data.
  • Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices.

Required Qualifications
  • 5+ years of experience building and deploying production software, ML systems, or AI platforms.
  • 1+ years of hands-on experience building production Generative AI or LLM-based applications.
  • Strong programming skills in Python and experience with software engineering best practices.
  • Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent.
  • Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks.
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies.
  • Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP.
  • Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures.
  • Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure.
  • Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices.
  • Experience building monitoring, observability, and alerting solutions for ML and AI systems.
  • Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations.
  • Experience designing secure, scalable, production-ready AI platforms and services.
  • Strong communication and collaboration skills with the ability to work across technical and business teams.

Preferred Qualifications
  • Previous experience implementing Generative AI and MLOps solutions within healthcare environments.
  • Experience working with EPIC or healthcare interoperability platforms.
  • Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices.
  • Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling.
  • Experience with GPU infrastructure optimization and scalable inference architectures.
  • Familiarity with multi-agent AI systems and autonomous workflows.
  • Experience with event-driven architectures, streaming pipelines, and real-time inference systems.
  • Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies.
  • Experience with enterprise AI platform architecture and internal developer platforms.
  • Prior experience mentoring engineers and leading technical initiatives.

Education
  • 5+ years of relevant experience with a degree (Required)

or
  • 7+ years of relevant experience without a degree (Required)
  • Experience in lieu of Bachelor's Degree.

Certification/Licensure
  • No specific certification or licensure requirements

Experience
  • 5 to 7 years of relevant experience

We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: 91,416.00 - 152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities.
Keywords: Talroo-IT, MLOps, Gen AI, LLM, AWS, Azure, GCP, AI/ML, Python, PyTorch, Hugging Face Transformers, TensorFlow, RAG, EPIC, HIPAA, AI Governance
Benefits: Caring For Your Family and Your Career
Medical, Dental, Vision plans
• Adoption, Fertility and Surrogacy Reimbursement up to 10,000
• Paid Time Off and Sick Leave
• Paid Parental & Family Caregiver Leave
• Emergency Backup Care
• Long-Term, Short-Term Disability, and Critical Illness plans
• Life Insurance
• 401k/403B with Employer Match
• Tuition Assistance - 5,250/year and discounted educational opportunities through Guild Education
• Student Debt Pay Down - 10,000
• Reimbursement for certifications and free access to complete CEUs and professional development
• Pet Insurance
• Legal Resources Plan
• Colleagues have the opportunity to earn an annual discretionary bonus if established system and employee eligibility criteria is met.
Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves.
In support of our mission "to improve health every day," this is a tobacco-free environment.
For positions that are available as remote work, Sentara Health employs associates in the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

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