{"id":1541341,"url":"https://alion.io/job/st-engineering-ai-solution-architect-2","title":"AI Solution Architect","company":{"id":1818473,"name":"ST Engineering","domain":"stengg.com","url":"https://alion.io/company/stengg","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":63000,"max_usd":122000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CrewAI","optional":false},{"name":"GCP","optional":false},{"name":"Java","optional":false},{"name":"LangChain","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-09-30T21:10:40Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-10T22:53:04Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"JOB RESPONSIBILITIES\nWe are seeking a forward-thinking AI Solution Architect to lead the design, evaluation, and rollout of cutting-edge Agentic AI applications across the enterprise. The role requires both technical depth and business acumen, with the ability to identify opportunities, conceptualize solutions, and drive implementation-whether by building in-house or integrating with best-in-class external platforms.\nThe ideal candidate will possess a deep understanding of the Agentic AI ecosystem, be comfortable navigating the rapidly evolving world of large language models (LLMs), and demonstrate strong technical, solution-selling, and leadership skills\nKey Responsibilities\n AI Solution Design & Architecture\nIdentify and evaluate opportunities to implement Agentic AI solutions aligned with business strategy.\nConceptualize and architect AI applications leveraging both in-house development and vendor solutions (“make or buy” approach).\nEnsure scalable, secure, and compliant AI solution designs that integrate seamlessly into enterprise IT and data platforms.\n Agentic AI Ecosystem Ownership\nDefine and maintain the blueprint for an Agentic AI ecosystem-including LLMs, Retrieval-Augmented Generation (RAG), prompt engineering frameworks, MLOps, orchestration tools, and monitoring.\nPartner with data engineering, and cybersecurity teams to ensure robust infrastructure and governance.\nImplementation & Rollout\nBuild, test, and deploy Agentic AI applications for diverse use cases across ST Engineering business units.\nManage solution pilots, proof-of-concepts, and enterprise-wide rollout projects.\nEstablish the best practices and reusable frameworks for Agentic AI adoption.\nStakeholder Engagement & Solution Selling\nCollaborate with business leaders to translate business needs into AI solutions.\nPresent AI solution proposals to senior stakeholders in clear, impactful ways, highlighting value, ROI, and risk considerations.\nDrive adoption and organizational buy-in through effective communication and change management.\nLeadership & Collaboration\nWork closely with cross-functional teams including IT, Data Science, and business units.\nMentor and guide team members on Agentic AI techniques, frameworks, and best practices.\nChampion a collaborative, innovative, and learning-oriented culture.\nJob Requirements:\nMust-Have:\nProven experience architecting and implementing enterprise-scale Agentic AI solutions.\nStrong expertise in:Large Language Models (LLMs) and multimodal models.\nPrompt engineering strategies and frameworks.\nRetrieval-Augmented Generation (RAG).\nMLOps, model deployment, and lifecycle management.\n\nStrong expertise with agentic AI frameworks (LangChain, CrewAI, AutoGen, etc.).\nExcellent programming skills (e.g., Python, Java, or equivalent).\nStrong communication and solution-selling skills-capable of engaging both technical and business stakeholders.\nDemonstrated ability to lead and work within multi-disciplinary teams.\nProficiency in English, both written and spoken.\nStrong problem-solving skills with a balance of strategic vision and execution focus.\nHands-on exposure to cloud-based AI/ML platforms (AWS, Azure, GCP).\nPrior experience in enterprise IT transformation or digital innovation programs.\nPlus:\nKnowledge of enterprise data platforms, APIs, and systems integration.\nExperience in Data Science and Machine Learning model development.\nIndustry certifications in AI/ML, cloud, or enterprise architecture.","description_format":"text","description_chars":3461,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Cybersecurity","Military"],"lifecycle":[{"event":"open","at":"2026-09-30T21:10:40Z"}],"visa":[],"liveness":{"score":75,"band":"hot","label":"Hiring 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