{"id":949050,"url":"https://alion.io/job/nextgen-federal-systems-generative-ai-engineer","title":"Generative AI Engineer","company":{"id":7117,"name":"NextGen Federal Systems","domain":"nextgenfs.com","url":"https://alion.io/company/nextgenfs","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":86,"open_postings":16,"ghost_share":0,"stale_share":0.563,"repost_share":0,"time_to_fill_p50_days":54,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":130000,"max_usd":285000,"period":"year","method":"role_country_seniority_unknown","sample_n":4027},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Embeddings","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Office","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"NumPy","optional":false},{"name":"Outlook","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Bitbucket","optional":true},{"name":"CI/CD","optional":true},{"name":"Configuration Management","optional":true},{"name":"Docker","optional":true},{"name":"Git","optional":true},{"name":"GitHub","optional":true},{"name":"GitLab","optional":true},{"name":"Hallucination","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Reranking","optional":true},{"name":"Terraform","optional":true},{"name":"Tool Use","optional":true}],"status":"live","first_seen_at":"2026-05-08T19:25:50Z","employer_posted_date":"2026-05-08","last_verified_at":"2026-10-18T11:26:55Z","board_verified":true,"closed_at":null,"days_open":162,"trust":{"level":"stale","repost_count":1,"flags":["stale"],"days_open":162},"description":"NextGen Federal Systems, LLC. is seeking a Generative AI/Machine Learning Engineer to research, design, develop, and deploy innovative AI/ML and Generative AI solutions across a variety of mission-focused problem sets. The selected candidate will support the development of advanced AI capabilities using technologies such as large language models, retrieval-augmented generation, Model Context Protocol servers, agentic workflows, and cloud-native AI services including AWS Bedrock.\nThe selected candidate will be part of a distributed development team operating in a dynamic, agile, fast-paced environment and will participate in all phases of the software engineering lifecycle, including research, requirements analysis, solution design, model development, integration, deployment, evaluation, and testing.\nQualifications:\nBachelor's [Master's / PhD] Degree in Computer Science, Math, Engineering, or related field\n6+ [4+ / 2+] years of work-related experience with applied machine learning, data science, software engineering, or AI/ML system development\nExperience designing, developing, or deploying machine learning, Generative AI, or data-driven software solutions\nRequired Skills and Experience:\n· Work as part of a technical team to design, develop, implement, and transition AI/ML and Generative AI capabilities that meet client operational requirements\n· Experience developing solutions using Python and common AI/ML or data science libraries such as pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, LangChain, LlamaIndex, or similar frameworks\n· Familiarity with large language models and Generative AI concepts, including prompt engineering, embeddings, vector databases, retrieval-augmented generation, model evaluation, and responsible AI considerations\n· Experience designing or integrating LLM-based applications, including chat-based interfaces, document question-answering systems, workflow automation, summarization tools, or AI-enabled decision-support systems\n· Experience using cloud services to build, deploy, or manage AI/ML solutions\n· Understanding of machine learning concepts, including data preprocessing, feature engineering, model training, model evaluation, performance metrics, and model deployment best practices\n· Strong written and verbal communication skills, including the ability to explain technical concepts to both technical and non-technical stakeholders\n· Proficiency with Microsoft Office tools, including Word, Excel, PowerPoint, and Outlook\n*Secret Clearance\nDesired Skills and Experience:\nExperience working in an Agile development lifecycle\nExperience developing Generative AI solutions using AWS Bedrock, including foundation models, Knowledge Bases, Agents, Guardrails, or related AWS AI/ML services\nFamiliarity with Model Context Protocol and the development or integration of MCP servers, tools, resources, or agent-accessible services\nExperience with retrieval-augmented generation architectures, including document ingestion, chunking strategies, embedding models, vector databases, metadata filtering, reranking, and response evaluation\nExperience with agentic AI workflows, tool-calling, function-calling, multi-step reasoning 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