{"id":1759644,"url":"https://alion.io/job/reisystems-aiml-llm-engineer","title":"AI/ML & LLM Engineer","company":{"id":1962699,"name":"Reisystems","domain":"reisystems.com","url":"https://alion.io/company/reisystems","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sterling, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":122000,"max_usd":232000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":987},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Scrum","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Amazon S3","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Azure","optional":true},{"name":"C#","optional":true},{"name":"Chroma","optional":true},{"name":"FAISS","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"OpenAI","optional":true},{"name":"OpenSearch","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Semantic Kernel","optional":true}],"status":"live","first_seen_at":"2026-10-03T12:15:39Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-07T23:18:05Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Overview\nREI Systems’ mission is to deliver reliable, innovative technology solutions that advance Federal clients' missions and exceed their expectations. Our technologists and consultants are passionate about solving complex challenges that impact millions of lives. We take a Mindful Modernization® approach in delivering our services, including application modernization, grants management, case management systems, government data analytics, and advisory services. This approach, the REI Way, ensures mission impact by aligning our clients' strategic objectives with measurable outcomes through people, processes, and technology. We offer the same commitment to our employees by providing professional development, meaningful projects, and flexibility to spend time with family and friends. We believe employees are at their best when fulfilled in both their professional careers and their personal lives. Learn more at www.REIsystems.com. Employees voted REI Systems a Washington Post Top Workplace in 2015, 2016, 2018, 2020, 2021, 2022, 2023, 2024, and 2025!\nResponsibilities\nPosition Overview\nREI Systems is seeking a mid-senior AI/ML & LLM Engineer to support technology modernization and digital transformation initiatives for the FDA.\nThe AI/ML & LLM Engineer will design, develop, evaluate, deploy, and support machine learning and Generative AI solutions that improve data analysis, automate business processes, enhance search and knowledge discovery, and support intelligent decision-making.\nThe ideal candidate combines strong Python, machine learning, and LLM engineering skills with practical experience building production-oriented RAG, NLP, and AI services. This role is intended for a hands-on engineer who can independently own complex AI development tasks while collaborating with data engineers, software developers, product owners, architects, cloud engineers, and business stakeholders.\nResponsibilities\nAI/ML Development\nDesign, develop, test, and implement machine learning and AI solutions to address business and operational requirements.\nDevelop machine learning models using structured, semi-structured, and unstructured datasets.\nBuild and maintain reusable Python components, APIs, services, notebooks, and AI/ML pipelines.\nPerform data preparation, feature engineering, model training, validation, testing, performance evaluation, and optimization.\nEvaluate algorithms, models, and approaches based on accuracy, robustness, performance, scalability, explainability, and business requirements.\nIntegrate AI/ML capabilities into existing enterprise applications and workflows through well-defined services and APIs.\nDevelop proof-of-concepts and prototypes and transition successful solutions into secure, production-ready capabilities.\nTroubleshoot model, data, integration, latency, and application issues throughout the development lifecycle.\nGenerative AI & LLM Solutions\nDevelop applications leveraging Large Language Models (LLMs) and Generative AI technologies.\nBuild and support Retrieval-Augmented Generation (RAG) solutions using enterprise documents, structured data, and approved knowledge sources.\nImplement prompt engineering, prompt templates, grounding, context management, tool/function calling, and structured LLM outputs.\nIntegrate commercial and/or open-source LLMs through APIs and enterprise AI platforms.\nWork with embeddings, semantic search, vector databases, reranking, chunking strategies, and document-processing pipelines.\nDevelop AI-enabled capabilities such as intelligent search, summarization, classification, information extraction, question-answering, and workflow automation.\nDesign and execute LLM evaluation approaches for accuracy, relevance, groundedness, consistency, safety, latency, and potential hallucinations.\nImplement appropriate guardrails, monitoring, fallback strategies, and human-in-the-loop processes for Generative AI applications.\nRAG, Knowledge & Data Engineering\nDesign ingestion and retrieval pipelines for enterprise documents and data sources used by AI/LLM applications.\nDevelop data preprocessing, cleansing, transformation, chunking, metadata enrichment, and validation routines.\nWork with relational databases, APIs, document repositories, object storage, search platforms, and cloud-based data services.\nWrite and optimize SQL queries and retrieval logic to support model training, evaluation, and inference.\nCollaborate with data engineers to establish reliable, governed data pipelines for AI/ML use cases.\nEnsure appropriate handling of data quality, lineage, security, access controls, and source traceability.\nMLOps, LLMOps & Deployment\nDeploy AI/ML models and LLM-enabled services into development, test, and production environments.\nDevelop and maintain model inference APIs, AI services, and microservices using production software engineering practices.\nBuild or support automated model testing, evaluation, deployment, monitoring, and retraining pipelines.\nTrack model and prompt versions, evaluation results, configurations, dependencies, and production behavior.\nMonitor model quality, retrieval quality, latency, cost, drift, failures, and other operational metrics and recommend improvements.\nParticipate in CI/CD processes for AI/ML applications and containerize services using technologies such as Docker.\nCollaborate with DevOps and cloud engineering teams to deploy scalable, observable, and resilient AI solutions.\nResponsible AI, Security & Governance\nApply responsible AI practices including transparency, traceability, evaluation, testing, documentation, and appropriate human oversight.\nEvaluate AI solutions for bias, accuracy, reliability, privacy, security, data leakage, prompt injection, and other relevant risks.\nImplement safeguards appropriate to the use case, including input/output controls, content filtering, grounding checks, access controls, and auditability.\nFollow applicable federal and FDA security, privacy, data-governance, records-management, and software development requirements.\nMaintain technical documentation covering models, prompts, data sources, evaluation methods, configurations, limitations, testing, and deployment.\nParticipate in technical and governance reviews and provide documentation required for production deployment and operational support.\nSoftware Engineering & Agile Delivery\nDevelop clean, maintainable, testable, and reusable Python code following established software engineering standards.\nDevelop RESTful APIs and backend services that expose AI/ML functionality to enterprise applications.\nParticipate in code reviews, unit testing, integration testing, technical design discussions, and documentation.\nWork within Agile/Scrum development teams and participate in sprint planning, backlog refinement, demonstrations, and retrospectives.\nCollaborate with application developers to integrate AI functionality into Java, .NET, web, and cloud-based enterprise applications without assuming ownership of the full application stack.\nQualifications\nApproximately 5-8 years of professional software development, data engineering, data science, AI/ML, or related technical experience, including substantial hands-on AI/ML development experience.\nStrong programming skills in Python and experience building production-quality Python applications or services.\nHands-on experience with machine learning libraries/frameworks such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, or similar technologies.\nExperience developing, evaluating, and integrating AI/ML models into applications or production environments.\nHands-on experience with Generative AI, LLMs, NLP, and LLM APIs.\nStrong understanding of RAG, embeddings, vector search, prompt engineering, grounding, context management, and LLM evaluation.\nExperience working with structured and unstructured data, including preprocessing, transformation, validation, and analysis.\nExperience developing REST APIs and backend services for AI/ML functionality.\nWorking knowledge of SQL and relational databases.\nFamiliarity with Git, CI/CD, automated testing, containerization, and modern software development practices.\nExperience working in Agile, multidisciplinary development environments.\nStrong analytical, experimentation, troubleshooting, and problem-solving skills.\nAbility to communicate AI/ML concepts, limitations, risks, and recommendations clearly to technical and non-technical stakeholders.\nPreferred Qualifications\nExperience supporting FDA, HHS, or other federal government programs.\nExperience developing and deploying AI/ML solutions in AWS or Azure.\nExperience with AWS AI/ML services such as Amazon Bedrock, SageMaker, Lambda, S3, OpenSearch, or related services.\nExperience with Azure AI services or Azure OpenAI.\nExperience with vector databases or vector search technologies such as Pinecone, FAISS, OpenSearch, pgvector, Chroma, or similar technologies.\nExperience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI orchestration frameworks.\nExperience developing document intelligence, NLP, semantic search, knowledge-management, or enterprise search solutions.\nExperience designing automated LLM evaluation, prompt/version management, guardrails, or LLMOps capabilities.\nExperience with Docker and containerized AI application deployment; familiarity with Kubernetes or cloud-native environments.\nExperience with MLOps, model monitoring, model versioning, experiment tracking, or ML lifecycle management.\nUnderstanding of microservices, event-driven integration, and enterprise application architecture.\nFamiliarity with DevSecOps practices and secure software development for AI-enabled systems.\nExperience working with sensitive, regulated, scientific, healthcare, or federal datasets is a plus.\nProfessional Skills\nStrong analytical and critical-thinking abilities.\nExcellent written and verbal communication skills.\nAbility to translate business requirements into practical AI/ML and LLM-enabled solutions.\nAbility to independently own complex AI development tasks while collaborating effectively within a larger technical team.\nStrong attention to detail and commitment to model, software, evaluation, and data quality.\nAbility to balance experimentation with production engineering, security, governance, performance, and operational constraints.\nAbility to communicate technical risks, assumptions, model limitations, dependencies, and recommendations clearly.\nStrong documentation, mentoring, and knowledge-sharing skills.\nKey Technologies\nLanguages: Python, SQLAI/ML: Scikit-learn, PyTorch, TensorFlow, Hugging FaceGenerative AI: LLMs, RAG, Prompt Engineering, Embeddings, Vector Search, LLM EvaluationAI Orchestration: LangChain, LlamaIndex, Semantic Kernel or comparable frameworksCloud: AWS and/or AzureDevelopment: REST APIs, Git, CI/CD, DockerData: SQL databases, APIs, document repositories, structured and unstructured dataMethodology: Agile/Scrum, MLOps/LLMOps, DevSecOps\nIdeal Candidate Profile\nThe successful candidate will be a hands-on AI/ML and LLM engineer rather than solely a researcher, data analyst, or AI strategist. They should be comfortable writing production-quality Python, working with data, building and evaluating ML/LLM solutions, implementing RAG pipelines, developing AI APIs, and collaborating with application and cloud engineering teams to move AI capabilities from prototype into secure production environments.\nThis individual should have sufficient AI/ML experience to independently own complex development and evaluation tasks, make sound implementation recommendations, contribute to architecture and technical reviews, and mentor less-experienced engineers while working under the broader direction of senior architects and program leadership.\nEducation: Bachelor’s degree in Computer Science, Data Science, or a related field; Master’s degree preferred.\nLocation: Hybrid - Sterling, VA HQ (with flexibility for remote work as per company policy).\nClearance: Candidate must be able to obtain and mainta...","description_format":"text","description_chars":12075,"description_truncated":true,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Professional development"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Cybersecurity"],"lifecycle":[{"event":"open","at":"2026-10-03T12:15:39Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 39 · green card filings: 9","filings_12m":39,"filings_prev_12m":79,"green_card_filings_12m":9,"median_offered_wage_usd":142813,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":26}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":39,"reasons":["conf:1","velocity","win:early","comp:attention"],"computed_at":"2026-10-07T05:47:15Z"},"pay":null,"html_url":"https://alion.io/job/reisystems-aiml-llm-engineer","json_url":"https://alion.io/job/reisystems-aiml-llm-engineer.json","meta":{"generated_at":"2026-10-08T01:01:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1723,"day_limit":5000,"remaining_today":3277,"minute_limit":60,"resets_at":"2026-10-09T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1962699},"rest":"https://alion.io/mcp/rest/get_company?id=1962699"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Freisystems-aiml-llm-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Freisystems-aiml-llm-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Freisystems-aiml-llm-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/reisystems-aiml-llm-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Freisystems-aiml-llm-engineer"}]}