{"id":2668003,"url":"https://alion.io/job/relisource-generative-ai-solutions-architect","title":"Generative AI Solutions Architect","company":{"id":4436043,"name":"ReliSource","domain":"relisource.com","url":"https://alion.io/company/relisource","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dhaka, Bangladesh"],"countries":["BD"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":35000,"max_usd":84000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1519},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Docker","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"LM Studio","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Ollama","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"vLLM","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"BigQuery","optional":true},{"name":"Google BigQuery","optional":true},{"name":"MLFlow","optional":true},{"name":"PyTorch","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Snowflake","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-10-16T03:22:33Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-16T22:14:16Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Application Deadline\nOctober 31, 2026 (Early applications will be given preference)\nJob Location\nGulshan-1, Dhaka\nNumber of Vacancies: 2\nWho are we looking for?\nWe are looking for an experienced Generative AI Solutions Architect who can design, build, and scale production-grade LLM-powered, AI-assisted, and machine learning solutions.\nEducational Requirements\nB.Sc. in Computer Science & Engineering, any other engineering discipline, Mathematics, Statistics, or a similar field from a reputed university.\nNote: Education requirements are not limited to the above. Candidates with the right skills and experience are encouraged to apply.\nExperience Requirements\nThe ideal candidate will have 8+ years of professional experience in AI engineering, machine learning, software engineering, advanced analytics, or related fields, with experience in technical architecture or technical leadership roles.\nOverview of the Responsibilities\nArchitect and deliver production-grade Generative AI and ML systems.\nBuild reliable, scalable, and maintainable AI solutions from experimentation to production.\nDesign and support practical Generative AI use cases such as LLM-powered applications, AI assistants, RAG, and agentic workflows.\nTranslate business and client requirements into practical AI solution architectures.\nWork with Data Scientists, Data Engineers, and Software Engineers to turn prototypes into production-ready systems.\nGuide teams on responsible use of AI tools such as GitHub Copilot, Claude Code, Codex, OpenClaw, and similar platforms.\nMentor software teams and help them use Generative AI tools effectively in their day-to-day engineering work.\nDefine and improve LLMOps and MLOps practices, including deployment, monitoring, evaluation, retraining, and feedback loops.\nBuild CI/CD pipelines for AI/ML workflows, including data validation, feature engineering, model validation, prompt evaluation, and drift detection.\nKey Requirements\nPractical experience designing LLM-powered applications such as AI assistants, RAG systems, agentic workflows, or AI-assisted engineering tools.\nStrong knowledge of LLM APIs and/or locally hosted LLMs, including tools such as LM Studio, Ollama, vLLM, Hugging Face, Azure OpenAI, or similar platforms.\nExperience with LangSmith, LangChain, LangGraph, foundation models, RAG, MCP, vector databases, or prompt evaluation.\nHands-on experience with production ML/AI systems and MLOps or LLMOps practices.\nExperience with orchestration and containerization tools such as Docker, Kubernetes, or similar.\nHands-on experience with monitoring, evaluation, drift detection, and feedback loops in production environments.\nExperience using tools such as GitHub Copilot, Claude Code, Codex, OpenClaw, or similar tools.\nAbility to review, debug, test, and validate AI-generated code before using it in production.\nAbility to mentor engineers and explain Generative AI concepts in a practical, easy-to-understand way.\nStrong programming skills in Python or similar languages.\nAbility to use cutting edge technologies like AI to efficiently deliver tasks.\nNice To Have Requirements\nStrong experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.\nExperience with internal AI assistant development, AI coding workflows, or enterprise AI enablement.\nExposure to recommendation systems, search, or personalization platforms.\nExposure to data warehouses such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse.\nNotable experience in Kaggle or other machine learning competitions.\nHands-on expertise in MLOps tooling such as MLflow, SageMaker, or similar.\nWhat's in it for you?\nLead cross-functional teams and establish enterprise-wide AI best practices.\nOpportunity to architect mission-critical AI/ML solutions for global clients.\nVery competitive salary and excellent career opportunity in a focused and stable organization.\nMost importantly, a friendly work environment with opportunity to learn from a number of highly skilled 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