{"id":3486662,"url":"https://alion.io/job/pavago-ai-engineer-2","title":"AI Engineer","company":{"id":1117,"name":"Pavago","domain":"pavago.co","url":"https://alion.io/company/pavago","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":199,"ghost_share":0,"stale_share":0.99,"repost_share":0,"time_to_fill_p50_days":33,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"US time zones","utc_offset_min":-8,"utc_offset_max":-5},"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-29T21:51:48Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-31T07:53:41Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Position Type: Full-Time | Remote\nWorking Hours: U.S. Business Hours\nAbout the Role\nWe’re looking for a skilled AI Engineer to build, deploy, and improve AI-powered systems and features. You’ll work across the full development lifecycle, from prototyping and model development to production deployment, integration, and performance monitoring.\nThe ideal candidate has strong Python and machine learning skills, practical experience with NLP or LLM-based applications, and the ability to turn AI concepts into reliable, scalable products. You should be comfortable working independently, making technical decisions, and continuously improving deployed systems.\nKey Responsibilities\nAI Model Development\nDesign, build, and iterate on AI-powered systems and features.\nDevelop prototypes and turn successful experiments into production-ready solutions.\nApply machine learning techniques to solve practical product and customer problems.\nPipeline Architecture & Performance\nDesign and maintain reliable, scalable data and model inference pipelines.\nOptimize AI systems for performance, reliability, and efficiency.\nIdentify and resolve bottlenecks across data processing and model execution.\nIntegration & Deployment\nIntegrate AI models into existing product infrastructure and software systems.\nManage the process from experimentation and testing through deployment and monitoring.\nWork with APIs and supporting infrastructure to ensure smooth integration.\nApplied AI Research & Development\nStay current with developments in AI, machine learning, NLP, and LLMs.\nEvaluate new techniques and tools for practical use within the existing technical stack.\nTranslate relevant research and advancements into measurable product improvements.\nQuality, Evaluation & Iteration\nMonitor deployed model performance and diagnose issues.\nEvaluate models against benchmarks and defined quality criteria.\nDrive continuous improvement through systematic testing, evaluation, and retraining where appropriate.\nDocument technical approaches, findings, and implementation decisions.\nCross-Functional Collaboration\nWork with the technical team to align AI capabilities with product goals.\nContribute to architecture decisions and technical roadmaps.\nCommunicate progress, technical challenges, and potential blockers proactively.\nRequired Experience & Skills\nProven hands-on experience building and deploying AI or machine learning systems in a professional environment.\nStrong proficiency in Python.\nExperience with machine learning frameworks such as TensorFlow, PyTorch, or equivalent.\nSolid understanding of NLP, large language models (LLMs), or conversational AI, with practical product implementation experience.\nFamiliarity with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.\nExperience with model hosting, deployment, scaling, and monitoring.\nStrong understanding of APIs and integrating AI components into broader software systems.\nAbility to evaluate model performance, troubleshoot issues, and improve system reliability.\nClear written and verbal English communication skills.\nPerfect Fit / Culture\nYou’ll thrive in this role if you take ownership of technical challenges, make thoughtful decisions when requirements are unclear, and proactively communicate progress in a remote, asynchronous environment.\nYou should be curious about emerging AI technologies, committed to producing high-quality work, and practical about balancing technical excellence with delivering working solutions.\nTypical Day\nReview team updates, product requirements, and feedback on deployed models.\nRefine AI workflows, prompt pipelines, or inference systems.\nDebug integrations and evaluate model performance against benchmarks.\nDevelop and test AI features using Python and relevant ML frameworks.\nCollaborate with the technical team on architecture and priorities.\nDeploy code, document technical decisions, and flag blockers.\nIdentify opportunities to improve model quality, reliability, and performance.\nInterview Process\nAI Screening\nClient Interview\nOffer Stage\n#LI-AG1","description_format":"text","description_chars":4068,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate 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