{"schemaVersion":"jobsearcher.job.v1","id":"3bd11abe562a3709893174dd","url":"https://jobsearcher.com/jobs/3bd11abe562a3709893174dd","canonicalUrl":"https://jobsearcher.com/jobs/3bd11abe562a3709893174dd","title":"Principal Software Developer","description":"Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA\r\nWorkplace Type: Remote\r\nReq Id: 2909\r\nPosition Overview\r\nWe are seeking a motivated AI/ML Engineer to build reliable, scalable systems and Generative AI and Agentic AI features, and build and deploy data-driven solutions for our document-based compliance management platform. This role requires a technical expert who can develop, deploy, and maintain ML systems in production environments.\r\nKey Responsibilities\r\nBuild and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and inference pipelines with optimization of latency and cost\r\nDesign agentic AI systems that autonomously handle compliance workflows, document review, regulatory mapping, and multi-step reasoning tasks\r\nIntegrate comprehensive LLM evaluation frameworks with development and production systems\r\nBuild and operate end-to-end MLOps pipelines, deployment systems, monitoring, and rollbacks workflows\r\nImplement explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency and regulatory adherence\r\nCollaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders\r\nEducation / Qualifications\r\nTechnical Skills\r\nPython (5+ years): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest\r\nSQL: Advanced proficiency with complex queries, window functions, and optimization\r\nMachine Learning & NLP: Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis\r\nGenerative AI & LLMs: Hands-on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma)\r\nMLOps & ModelOps: End-to-end experience with ML pipelines, model versioning, feature stores, drift detection, CI/CD for ML, and Docker containerization\r\nLLM Evaluation: Experience with evaluation frameworks (RAGAS, DeepEval), custom metrics, benchmark datasets, and human-in-the-loop validation\r\nCloud & AWS: Experience with AWS services including SageMaker, Bedrock, S3, Lambda, EC2, and CloudWatch\r\nStatistics & Experimentation: Strong foundation in statistics, A/B testing, causal inference, and experimental design\r\nVisualization: Proficiency with Tableau, Power BI, or Python visualization libraries\r\nExperience & Education\r\n5+ years in data science, ML engineering, or related roles\r\n3+ years building NLP/generative AI applications and implementing MLOps in production\r\nBachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field\r\nTrack record of deploying ML systems processing large-scale datasets with proper monitoring and governance\r\nPreferred Qualifications\r\nExperience with agentic AI frameworks (LangGraph, LangChain, AutoGen, CrewAI)\r\nKnowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems\r\nFamiliarity with big data tools (Spark, Databricks, Snowflake), orchestration (Airflow, Kubeflow), and monitoring tools (Datadog, Prometheus)\r\nExperience with LLM fine-tuning, document processing libraries, multi-modal AI, or distributed training\r\nUnderstanding of ML governance, bias detection, model risk management, and data privacy regulations (GDPR, CCPA, HIPAA)\r\nExperience working in agile environments with Jira\r\nAWS ML certifications or similar credentials\r\nKey Competencies\r\nStrong communication skills explaining complex models to technical and nontechnical audiences\r\nAbility to work independently and collaboratively in fast-paced environments\r\nProven ability to convert POCs into production-grade solutions\r\nUnderstanding of ethical AI and building trustworthy, explainable systems for regulated environments\r\nWhat You'll Build\r\nLLM evaluation frameworks ensuring 95%+ accuracy for compliance-critical features\r\nPrompts for LLMs to achieve specific, high-quality outcomes\r\nAgentic AI systems autonomously handling document review and compliance workflows\r\nGenAI document understanding features processing millions of regulatory documents\r\nPredictive models identifying compliance risks before they occur\r\nReal-time semantic search and explainable ML systems meeting regulatory requirements\r\nProduction MLOps pipelines supporting dozens of models with automated monitoring and retraining\r\nGrowth Opportunities\r\nDrive adoption of emerging AI technologies and establish best practices\r\nMentor ML engineers\r\nShape AI/ML roadmap and establish center of excellence for compliance AI\r\nCollaborate with product leadership on long-term vision for AI-powered compliance\r\nJ-18808-Ljbffr","company":"Octave","rawCompany":"octave","city":"El Paso","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-06-26T02:21:31.742Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Principal Software Developer","description":"Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA\r\nWorkplace Type: Remote\r\nReq Id: 2909\r\nPosition Overview\r\nWe are seeking a motivated AI/ML Engineer to build reliable, scalable systems and Generative AI and Agentic AI features, and build and deploy data-driven solutions for our document-based compliance management platform. This role requires a technical expert who can develop, deploy, and maintain ML systems in production environments.\r\nKey Responsibilities\r\nBuild and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and inference pipelines with optimization of latency and cost\r\nDesign agentic AI systems that autonomously handle compliance workflows, document review, regulatory mapping, and multi-step reasoning tasks\r\nIntegrate comprehensive LLM evaluation frameworks with development and production systems\r\nBuild and operate end-to-end MLOps pipelines, deployment systems, monitoring, and rollbacks workflows\r\nImplement explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency and regulatory adherence\r\nCollaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders\r\nEducation / Qualifications\r\nTechnical Skills\r\nPython (5+ years): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest\r\nSQL: Advanced proficiency with complex queries, window functions, and optimization\r\nMachine Learning & NLP: Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis\r\nGenerative AI & LLMs: Hands-on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma)\r\nMLOps & ModelOps: End-to-end experience with ML pipelines, model versioning, feature stores, drift detection, CI/CD for ML, and Docker containerization\r\nLLM Evaluation: Experience with evaluation frameworks (RAGAS, DeepEval), custom metrics, benchmark datasets, and human-in-the-loop validation\r\nCloud & AWS: Experience with AWS services including SageMaker, Bedrock, S3, Lambda, EC2, and CloudWatch\r\nStatistics & Experimentation: Strong foundation in statistics, A/B testing, causal inference, and experimental design\r\nVisualization: Proficiency with Tableau, Power BI, or Python visualization libraries\r\nExperience & Education\r\n5+ years in data science, ML engineering, or related roles\r\n3+ years building NLP/generative AI applications and implementing MLOps in production\r\nBachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field\r\nTrack record of deploying ML systems processing large-scale datasets with proper monitoring and governance\r\nPreferred Qualifications\r\nExperience with agentic AI frameworks (LangGraph, LangChain, AutoGen, CrewAI)\r\nKnowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems\r\nFamiliarity with big data tools (Spark, Databricks, Snowflake), orchestration (Airflow, Kubeflow), and monitoring tools (Datadog, Prometheus)\r\nExperience with LLM fine-tuning, document processing libraries, multi-modal AI, or distributed training\r\nUnderstanding of ML governance, bias detection, model risk management, and data privacy regulations (GDPR, CCPA, HIPAA)\r\nExperience working in agile environments with Jira\r\nAWS ML certifications or similar credentials\r\nKey Competencies\r\nStrong communication skills explaining complex models to technical and nontechnical audiences\r\nAbility to work independently and collaboratively in fast-paced environments\r\nProven ability to convert POCs into production-grade solutions\r\nUnderstanding of ethical AI and building trustworthy, explainable systems for regulated environments\r\nWhat You'll Build\r\nLLM evaluation frameworks ensuring 95%+ accuracy for compliance-critical features\r\nPrompts for LLMs to achieve specific, high-quality outcomes\r\nAgentic AI systems autonomously handling document review and compliance workflows\r\nGenAI document understanding features processing millions of regulatory documents\r\nPredictive models identifying compliance risks before they occur\r\nReal-time semantic search and explainable ML systems meeting regulatory requirements\r\nProduction MLOps pipelines supporting dozens of models with automated monitoring and retraining\r\nGrowth Opportunities\r\nDrive adoption of emerging AI technologies and establish best practices\r\nMentor ML engineers\r\nShape AI/ML roadmap and establish center of excellence for compliance AI\r\nCollaborate with product leadership on long-term vision for AI-powered compliance\r\nJ-18808-Ljbffr","datePosted":"2026-06-26T02:21:31.742Z","dateModified":"2026-06-26T02:21:31.742Z","hiringOrganization":{"@type":"Organization","name":"Octave","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"El Paso","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3bd11abe562a3709893174dd"},"url":"https://jobsearcher.com/jobs/3bd11abe562a3709893174dd"}}