{"id":2582038,"url":"https://alion.io/job/saic-aiml-platform-engineer","title":"AI/ML Platform Engineer","company":{"id":58788,"name":"SAIC","domain":"saic.com","url":"https://alion.io/company/saic","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":81,"open_postings":54,"ghost_share":0,"stale_share":0.963,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Front Royal, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":143000,"max_usd":272000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1213},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"CloudFormation","optional":false},{"name":"Databricks","optional":false},{"name":"FedRAMP","optional":false},{"name":"Hugging Face","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"NIST 800-53","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"FAISS","optional":true},{"name":"Function Calling","optional":true},{"name":"Git","optional":true},{"name":"LiteLLM","optional":true},{"name":"MLFlow","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"OpenSearch","optional":true},{"name":"Pinecone","optional":true},{"name":"Tool Use","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-10-14T21:07:17Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T21:56:13Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"We are seeking a highly skilled AI/ML Platform Engineer to join our Engineering Team supporting Civilian government agency programs. This is not a role for someone who only builds AI solutions it is a role for someone who builds the platforms that enable others to build AI solutions, across all paradigms: traditional ML, Generative AI, and Agentic AI.\nThe vision is simple: mission teams should be able to focus entirely on their problems and the solutions they want to build and trust that the platform underneath them handles the tools, infrastructure, guardrails, governance, monitoring, and technical complexity. That platform is what this team builds and operates. The right candidate takes genuine satisfaction in being the force multiplier that makes everyone around them more capable.\nWe welcome engineers from commercial and federal backgrounds alike. If you've built serious AI/ML platforms in industry and want to apply that experience to problems that matter at scale, in a regulated environment, partnering with cloud leaders like AWS and Databricks this is that opportunity. The AI/ML landscape is evolving fast, and we move with it: new capabilities get evaluated, integrated, and delivered to mission teams at pace. The right candidate thrives in that environment, stays ahead of it, and drives change rather than waiting for direction.\nEqually important is an FDE (Field Delivery Engineer) mindset: partner directly with customers from concept through delivery requirements, specs, design, implementation, production. One engineer, full thread, done. Proactive by default, bringing solutions rather than status, and driving to completion without being managed to it.\nKey Responsibilities\nEnable AI/ML platform services as a governed, multi-tenant enterprise offering tenant onboarding, entitlements, access controls, compute environments, and service-level guardrails spanning traditional ML, GenAI, and agentic AI.\n\nEnable GenAI application building blocks governed access to frontier models via an AI gateway layer, RAG infrastructure (knowledge bases, vector databases, embedding pipelines), per-tenant guardrails, grounding validation, and feedback mechanisms so customers can build GenAI applications on a trusted foundation without reinventing the plumbing.\n\nEnable agentic AI patterns orchestration frameworks, tool/API integration, memory and state management, human-in-the-loop controls, and safety guardrails so customers can build and run agent-based workflows within the platform's governance boundary.\n\nEnable traditional ML operationalization governed training environments, model deployment pipelines with TAI controls (bias, fairness, explainability, model cards), and fleet-wide drift and quality monitoring across all operationalized models.\n\nPartner with customers from concept to delivery own the engagement end to end: requirements, specs, solution design, hands-on implementation, and production handoff. Sit with mission teams, understand their problems, and help them build on the platform.\n\nRapidly evaluate and integrate new platform capabilities stay current with the evolving AI/ML landscape, assess new tools and services, and bring the right ones into the platform offering at pace.\n\nBuild platform onboarding patterns and IaC templates (Terraform, CloudFormation) with SSO integration, designed for repeatability and portability across deployments.\n\nDevelop secure API-based model access and inference endpoints consistent with governance and security standards.\n\nDocument reusable patterns, frameworks, and APIs everything built is a starting point for the next deployment, not a one-off.\n Bachelor’s or master’s degree in computer science, Machine Learning, or a related field.\n\n5+ years of hands-on AI/ML engineering experience actively writing code, building pipelines, and architecting systems across traditional ML, GenAI, and/or agentic AI. Hands-on experience must be current; this is not a role for someone whose coding days are behind them.\n\nDemonstrated platform-level thinking experience enabling AI/ML capabilities as a managed service for a team or organization, not just building standalone solutions (e.g., governed multi-tenant compute, model deployment pipelines with guardrails, GenAI access layers, agentic orchestration infrastructure).\n\nStrong proficiency in Python and hands-on experience with core AI/ML libraries (PyTorch, TensorFlow, HuggingFace, LangChain or equivalent).\n\nHands-on experience with cloud-based AI/ML platforms (Databricks, SageMaker, or equivalent) model development, MLOps, data governance, and multi-tenant operationalization.\n\nHands-on experience with GenAI and LLM frameworks RAG pipelines, vector databases, embedding models, prompt engineering, and governed model access layers.\n\nStrong IaC and cloud engineering skills Terraform, CloudFormation, AWS-native services, enterprise SSO integration, and cloud security patterns.\n\nKnowledge of federal security and governance standards (FedRAMP, NIST 800-53, data isolation best practices).\n\nProven ability to work directly with customers translate ambiguous problem statements into requirements, specs, and working solutions end to end.\n\nMotivated to work in regulated environments comfortable with governance requirements and security standards; sees these as constraints to engineer around, not blockers.\nDesired Skills\n\nExperience with agentic AI frameworks multi-agent orchestration, tool use, memory/state management, human-in-the-loop design, and safety boundary enforcement.\n\nFamiliarity with AI gateway patterns (e.g., LiteLLM) for centralized, governed LLM access with swappable model backends.\n\nExperience with vector databases (Pinecone, FAISS, Weaviate, Amazon OpenSearch Vector).\n\nWorking knowledge of CI/CD and MLOps practices (MLflow, Git, Docker) and data governance in multi-tenant environments.\n\nExperience in federal, healthcare, financial services, or other regulated environments where governance and compliance are first-class engineering concerns.\n\nCuriosity and judgment to evaluate emerging LLMs, open-source GenAI tooling, and agentic frameworks and bring the right ones into a platform context at pace.","description_format":"text","description_chars":6174,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Digital Government","Systems Integrators","Engineering Services"],"lifecycle":[{"event":"open","at":"2026-10-15T02:14:33Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":0,"expected_fill_days":15,"reasons":["conf:3","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-15T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/saic-aiml-platform-engineer","json_url":"https://alion.io/job/saic-aiml-platform-engineer.json","meta":{"generated_at":"2026-10-16T00:09:39Z","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":261,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-17T00:00:00Z"}},"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":58788},"rest":"https://alion.io/mcp/rest/get_company?id=58788"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsaic-aiml-platform-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%2Fsaic-aiml-platform-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%2Fsaic-aiml-platform-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/saic-aiml-platform-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsaic-aiml-platform-engineer"}]}