{"id":1610803,"url":"https://alion.io/job/cas-senior-data-scientist-agentic-ai-llm-engineering","title":"Senior Data Scientist, Agentic AI & LLM Engineering","company":{"id":1756478,"name":"CAS","domain":"cas.org","url":"https://alion.io/company/cas-org","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"UltiPro","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Columbus, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":123000,"max_usd":234000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1213},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Context Engineering","optional":false},{"name":"GCP","optional":false},{"name":"Hallucination","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Tool Use","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Hugging Face","optional":true},{"name":"PyTorch","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-09-24T13:41:23Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-15T13:15:46Z","board_verified":true,"closed_at":null,"days_open":21,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":21},"description":"CAS uses unparalleled scientific content, specialized technology and unmatched human expertise to help R&D organizations across Commercial, Government and Academic sectors create groundbreaking innovations that benefit the world. As the Scientific Information Solutions Division of the American Chemical Society, CAS manages the largest curated reservoir of scientific knowledge, and for 119 years, has helped innovators mine, assess and apply that information to keep businesses thriving. The CAS team is global, diverse, endlessly curious and strives to make actionable scientific insights accessible to innovators worldwide.\nCAS is currently seeking a Senior Data Scientist focused on agentic AI development and large language model (LLM) engineering. This position will be located at our headquarters in Columbus, Ohio.\nThis role sits on the Data Analytics and Insights (DAI) team, which builds the AI that powers CAS's scientific information products. You will work on the systems behind the Newton research assistants in SciFinder and BioFinder, the natural-language query agent in IPFinder, predictive models that ship inside products, and AI-assisted content curation pipelines, alongside data engineers, product managers, and scientific domain experts.\nThis role requires a highly self-directed professional who can independently design, build, and evaluate agentic AI systems and LLM-powered applications that turn CAS's curated, provenanced scientific content into trustworthy research capabilities. The successful candidate will provide strategic input into product and platform ideation, drive complex technical initiatives from concept through production, and translate advanced AI engineering into tangible business value with minimal oversight, while providing technical direction to less-experienced scientists and engineers.\nKey Responsibilities\nAgentic AI & LLM System Development\nIndependently design, build, and productionize agentic AI systems - including multi-step, tool-using, and multi-agent workflows - that support scientific research tasks.\nDevelop retrieval-augmented generation (RAG) pipelines that ground model outputs in curated, provenanced scientific content.\nImplement and extend model-context and tool-integration frameworks (for example, the Model Context Protocol) to connect LLMs and agents to scientific data sources and external systems.\nApply prompt engineering, context engineering, and orchestration techniques to improve the reliability and quality of agentic and generative workflows.\nApplied AI Engineering & Model Adaptation\nFine-tune, adapt, and deploy large language models - including self-hosted, open-weight models - for domain-specific scientific tasks.\nDevelop and deploy machine learning models that ship inside CAS products, such as property, toxicity, or biologic developability prediction, using scientific judgment to inform feature design and validate model behavior.\nTake AI capabilities from prototype all the way through production: building the data, training, and inference pipelines, owning the deployment, and iterating after first release, not just the proof of concept.\nWork with engineering and product to put AI features in front of real users at scale, and stay accountable for how they behave once they're live.\nSet and hold the engineering standard for production AI: appropriate safeguards such as content-safety guardrails, entitlement-based access control, evaluation, and model fallback, delivered as clean, tested, well-documented software with unit, integration, and end-to-end tests, containerized development, and CI/CD.\nUse agentic software development tools such as Claude Code as a core part of the daily workflow, and set the team's practice for using them well.\nScientific Grounding & Evaluation\nDesign rigorous evaluation frameworks for LLM and agentic systems - measuring accuracy, faithfulness, and robustness, and distinguishing acceptable model variability from factual error.\nCritically evaluate scientific datasets and model outputs for quality, completeness, and scientific validity, applying domain understanding of chemistry, materials science, or the life sciences.\nEstablish trustworthy-AI practices that keep model outputs grounded in curated, provenanced scientific content rather than the model's own priors.\nBusiness Impact & Communication\nIndependently synthesize technical findings and present strategic recommendations to senior executives and C-level stakeholders.\nInfluence organizational and product decisions through compelling, data-driven narratives and demonstrations.\nRepresent CAS's AI work externally through client engagements, conference presentations, and publications.\nTechnical Leadership & Mentorship\nSet the technical direction for a team of data scientists and data engineers: the standards, patterns, and architecture for how agentic and LLM systems get built, spanning data and inference pipelines, model and prompt design, and deployment.\nOwn design and code review across that work, from model and prompt design through data pipelines and serving infrastructure, and raise the bar on quality, reliability, and reproducibility.\nMentor junior data scientists and AI/data engineers, and unblock them on difficult technical problems.\nSet the team's standards for AI engineering, evaluation, and responsible deployment.\nLead and influence cross-functional initiatives as part of a shared-services model, without direct people-management responsibility.\nShare knowledge across the team through demos, documentation, and internal learning sessions.\nQualifications\nRequired\nMaster's degree in Computer Science, Data Science, Chemistry, Materials Science, Chemical Engineering, or a related technical or scientific field with 6+ years of applied AI/ML or data science experience; a Bachelor's degree in one of those fields with 8+ years; or a PhD with 3+ years.\nAdvanced proficiency in Python and the modern AI engineering stack (for example, PyTorch, Hugging Face, vector databases, orchestration/agent frameworks, SQL, and cloud platforms).\nDemonstrated, hands-on experience building LLM-powered applications, agentic or multi-agent systems, and/or RAG pipelines - and taking them to real users in production, including the post-launch iteration that implies.\nExperience fine-tuning, adapting, or deploying large language models, including familiarity with self-hosted or open-weight models.\nWorking knowledge of evaluation methodology for generative and agentic systems (accuracy, faithfulness, and hallucination/variability management).\nAbility to work with scientific data and domain concepts - such as chemical or materials data, molecular representations, or life-sciences datasets - well enough to judge whether a system's outputs are accurate, defensible, and useful to working scientists, and to partner effectively with subject-matter experts.\nExceptional communication skills, with a proven ability to influence senior stakeholders and lead cross-functional efforts.\nStrong project-management capability across multiple concurrent initiatives.\nExperience deploying and operating production systems in at least one cloud environment (AWS, Azure, or GCP).\nProficiency with agentic software development tools (for example, Claude Code or similar AI-assisted development environments).\nPreferred\nPhD in a computational, physical, chemical, or life-sciences field.\nExperience with tool-use and integration frameworks such as the Model Context Protocol (MCP).\nExperience self-hosting or serving open-weight models in production (LLMOps / MLOps).\nCheminformatics experience or familiarity with molecular representations and scientific databases.\nExperience building and deploying predictive ML models in a scientific or regulated domain.\nTrack record of publications or conference presentations in AI-for-science or applied machine learning.\nConsulting or client-facing experience in scientific, chemical, or life-sciences sectors.\nCAS offers a competitive salary and comprehensive benefits package, including a generous vacation plan, medical, dental, vision insurance plans, and employee savings and retirement plans. Candidates for this position must be authorized to work in the United States and not require work authorization sponsorship by our company for this position now or in the future. EEO/Minority/Female/Disabled/Veteran","description_format":"text","description_chars":8361,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Generous vacation","Retirement plans","Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Biotechnology"],"lifecycle":[{"event":"open","at":"2026-10-01T20:19:45Z"}],"visa":[],"liveness":{"score":68,"band":"ok","label":"Likely open","p_open":1,"p_active":0.751,"p_room":0.9,"age_days":20,"expected_fill_days":31,"reasons":["conf:0","velocity","win:mid"],"computed_at":"2026-10-15T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/cas-senior-data-scientist-agentic-ai-llm-engineering","json_url":"https://alion.io/job/cas-senior-data-scientist-agentic-ai-llm-engineering.json","meta":{"generated_at":"2026-10-15T16:30:05Z","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_verified","counted_by":"address","units_charged":1,"used_today":25176,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"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":1756478},"rest":"https://alion.io/mcp/rest/get_company?id=1756478"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fcas-senior-data-scientist-agentic-ai-llm-engineering"},{"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%2Fcas-senior-data-scientist-agentic-ai-llm-engineering"},{"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%2Fcas-senior-data-scientist-agentic-ai-llm-engineering"},{"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/cas-senior-data-scientist-agentic-ai-llm-engineering\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fcas-senior-data-scientist-agentic-ai-llm-engineering"}]}