{"id":3017403,"url":"https://alion.io/job/hed-ai-platform-engineer-2","title":"AI Platform Engineer","company":{"id":1967944,"name":"HED","domain":"hed.co","url":"https://alion.io/company/hed-co","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"ADP","truth_index":{"grade":"A","score":92,"open_postings":19,"ghost_share":0,"stale_share":0.105,"repost_share":0,"time_to_fill_p50_days":94,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Diego, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":170000,"currency":"USD","period":"year","gross":null,"usd_annual":170000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"AI Agents","optional":true},{"name":"Anthropic","optional":true},{"name":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"MLFlow","optional":true},{"name":"OpenAI","optional":true}],"status":"live","first_seen_at":"2026-10-21T16:03:00Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-25T00:47:19Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"AI Platform Engineer\nHED is hiring an AI Platform Engineer to develop, evaluate, and improve the AI capabilities that support our people and our practice.\nAbout HED\nWe are a team that is full of ideas, experience, creativity, passionate opinions, insatiable curiosity, uncompromising integrity, commitment, and skill. Our culture is about aspiration, embracing change and challenges, listening to (and learning from) each other, encouraging continual learning, and inspiring collective growth. As an inclusive, integrated architecture and engineering practice, we value the diversity of perspectives, experiences, abilities, and expertise that advance both the work we do, and the world we share.\nPosition Summary\nAt HED, we believe the most powerful solutions emerge when expertise, technology, and human insight come together. As a national integrated architecture and engineering firm, we are advancing how artificial intelligence connects knowledge, improves workflows, and empowers our people to deliver exceptional outcomes.\nYou will build and optimize production AI solutions, evaluate large language models, improve AI-generated responses, and transform organizational knowledge into secure, accessible, and actionable intelligence.\nWorking within our Data & AI team, you will own defined technical initiatives and collaborate with developers, data engineers, and business stakeholders. This role offers opportunities to influence technical decisions and grow into broader platform leadership.\nEssential Functions\nAI Model Evaluation and Performance\nDevelop and maintain model benchmarking, evaluation datasets, testing methods, and performance baselines across production AI applications.\nEvaluate models, prompts, and configurations against response quality, reliability, cost, latency, and risk; document findings and recommend improvements.\nSupport preproduction validation of model, prompt, and application changes.\nContext Engineering and AI Optimization\nDevelop and optimize retrieval-augmented generation (RAG), retrieval ranking, prompt structures, context management, and caching.\nMeasure answer quality, token usage, and operating costs; use results to guide improvements.\nCollaborate with application developers to improve shared AI capabilities and user experiences.\nAI Solution Development and Delivery\nDeliver defined AI use cases from requirements and design through implementation, testing, documentation, adoption, and improvement.\nHelp design workflows that capture and organize employee expertise, skills, and competencies for use in AI-powered applications.\nDevelop structured data models, skills taxonomies, and knowledge capture workflows; partner with data engineering to integrate governed datasets.\nWork with business stakeholders to define requirements, success criteria, and practical solutions.\nData Governance and Responsible AI\nApply privacy, security, data classification, consent, retention, and access-control requirements to AI solutions and datasets.\nSupport dataset quality, lineage, ownership, documentation, and auditability.\nTechnical Collaboration and Innovation\nContribute to architecture discussions, technical reviews, coding standards, automated testing, CI/CD, and code reviews.\nUse AI-assisted development tools responsibly and share technical knowledge with colleagues.\nEvaluate emerging generative AI and agentic technologies for practical application at HED.\nRequirements\nApproximately 4-6+ years of experience in software engineering, machine learning engineering, data engineering, or a related technical discipline.\nHands-on experience developing, deploying, or supporting LLM applications in production.\nExperience implementing AI evaluations, benchmarks, or performance testing.\nWorking knowledge of RAG, information retrieval, prompt engineering, and context optimization.\nProficiency in Python and SQL, Git, automated testing, and modern software development practices.\nExperience with cloud applications, APIs, and data integration workflows.\nUnderstanding of enterprise data governance, privacy, and security.\nAbility to independently deliver complex technical assignments and communicate effectively with technical and nontechnical stakeholders.\nPreferred Qualifications\nBachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related field, or equivalent practical experience.\nExperience with Azure OpenAI, Amazon Bedrock, Anthropic, or comparable AI platforms.\nFamiliarity with Databricks, Delta Lake, Unity Catalog, MLflow, or similar platforms.\nExperience with AI agents, automated workflows, experiment tracking, or multi-model systems.\nPhysical Requirements\nProlonged periods of sitting at a desk and working on a computer.\nMust be able to effectively communicate in writing and verbally via phone, video conferencing, and in person.\nVisual acuity to perform responsibilities.\nWork Environment\nWe embrace a hybrid model that promotes both autonomy and collaboration, including the freedom to work from home, with regular in-office days to connect with teammates and build culture.\nThe office is a professional, open-space environment designed for collaborative and independent work.\nOther Duties\nPlease note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. 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