{"id":3411179,"url":"https://alion.io/job/node-digital-intelligent-automationai-ml-engineer-full-stack-engineer","title":"Intelligent Automation/AI-ML Engineer (Full Stack Engineer)","company":{"id":5581,"name":"Node.Digital","domain":"node.digital","url":"https://alion.io/company/node-digital","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-28T05:59:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Herndon, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":137000,"max_usd":304000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Angular","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Agile","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Computer Vision","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"JavaScript","optional":true},{"name":"LLM","optional":true},{"name":"NLP","optional":true},{"name":"OCR","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-10-28T17:53:40Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-29T02:07:11Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Intelligent Automation/AI-ML Engineer (Full Stack Engineer)\nLocation: Herndon, VA (Hybrid Work)\nPreferred: US Citizenship\nExperience: 8+ yrs\nPosition Summary\nThe Intelligent Application / AI-ML Engineer is the architect and guardian of intelligent application solutions that incorporate AI/ML technologies using tools such as open source AI models. This role ensures the operational efficiency and continuous refinement of integrated AI/ML solutions across the organization. Responsibilities span the design, maintenance, and optimization of intelligent applications, including troubleshooting and resolving issues that arise after implementation.\nThe engineer will also explore new ways to embed artificial intelligence and machine learning into applications, supporting continuous improvement, learning, and augmented decision making. A key focus is building repeatable, reusable intelligent solutions for document processing, data cleansing, and similar use cases.\nKey Responsibilities\nSolution Design and Development\nDesign, build, and deploy intelligent application solutions that integrate AI/ML models with business workflows using modern development frameworks and open source AI models.\nDevelop repeatable, reusable components and services for document processing, data extraction, classification, and data cleansing.\nTranslate business requirements into technical designs, solution architectures, and documented standards.\nBuild end-to-end applications as a full stack engineer, including front-end user interfaces, backend servers and APIs, AI/ML models, databases, and business rules.\nDevelop and expose AI capabilities and tools through Model Context Protocol (MCP) servers so applications can use them in a consistent, reusable way.\nImplement business rules and decision logic that work alongside AI models, with clear governance, testing, and auditability.\nAI/ML Operations and Optimization\nManage the lifecycle of open source AI models, including deployment, versioning, monitoring, retraining, and retirement.\nMonitor model performance, accuracy, and drift, and tune solutions to maintain operational efficiency over time.\nImplement feedback loops (e.g., human-in-the-loop validation) to drive continuous learning and refinement.\nOptimize application performance, scalability, and resource utilization.\nSupport and Troubleshooting\nTroubleshoot and resolve post-implementation issues in open source AI models, ML pipelines, and integrated applications.\nPerform root cause analysis on production incidents and implement lasting fixes.\nMaintain runbooks, support documentation, and knowledge base articles.\nPartner with infrastructure, security, and platform teams to maintain a stable and compliant environment.\nCollaboration\nWork with business analysts, process owners, data teams, and IT to deliver solutions aligned with business goals.\nCommunicate progress, risks, and results clearly to technical and non-technical audiences.\nRequirements\nRequired Qualifications\nBachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field (or equivalent experience).\nExperience in intelligent application development, with hands-on experience building enterprise applications.\nWorking experience with open source AI models and document understanding techniques, or comparable AI/ML frameworks and tools.\nProficiency in Python and common ML libraries (e.g., scikit-learn, pandas, TensorFlow or PyTorch).\nUnderstanding of the ML lifecycle: data preparation, training, evaluation, deployment, monitoring, and retraining.\nExperience building document processing and data cleansing solutions.\nStrong troubleshooting and problem-solving skills in production environments.\nSolid knowledge of APIs, integrations, SQL, and data formats (JSON, XML, CSV).\nExcellent written and verbal communication skills.\nFull stack development experience: proficiency in Python and Java for backend services and APIs, and Angular for front-end user interfaces.\nHands-on experience with Model Context Protocol (MCP), including building or integrating MCP servers and tools.\nExperience designing and working with relational and/or NoSQL databases, including schema design and query optimization.\nPreferred Qualifications\nCloud, AI/ML, or software development certifications (e.g., advanced developer or solution architect credentials).\nExperience with OCR, NLP, computer vision, or generative AI/LLM integration.\nFamiliarity with cloud platforms (Azure, AWS, or GCP) and MLOps practices.\nKnowledge of Agile delivery, CI/CD, and source control (e.g., Git).\nUnderstanding of data governance, security, and responsible AI practices.\nBenefits\nMedical \nDental\nVision\nBasic Life \nHealth Saving Account\n401K Matching\nThree weeks of PTO/Sick\n11 Paid Holidays\nPre-Approved 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