{"id":1313761,"url":"https://alion.io/job/ryan-full-stack-ai-engineer","title":"Full Stack AI Engineer","company":{"id":1853398,"name":"Ryan","domain":"ryan.com","url":"https://alion.io/company/ryan-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"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":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":63000,"max_usd":180000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":585},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Claude Code","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"JavaScript","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-09-08T00:00:00Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-10-01T02:56:53Z","board_verified":true,"closed_at":null,"days_open":23,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":23},"description":"Why Ryan?\nCompetitive Compensation and Benefits\nBusiness Connectivity Reimbursement (Phone/Internet)\nGym Membership or Equipment Reimbursement\nLinkedIn Learning Subscription\nFlexible Work Environment\nTuition Reimbursement After One Year of Service\nAccelerated Career Path\nAward-Winning Culture & Community Outreach\nThe Full Stack AI Engineer is an early-career software engineering role focused on building and delivering full-stack applications with generative AI and agentic capabilities embedded into the solution architecture.\nThe role is designed for high-potential graduates and engineers with up to three years of experience who combine strong software engineering fundamentals with a different way of thinking about how AI can reshape enterprise workflows and applications.\nThis is not a traditional machine learning or data science role, and it is not about adding AI for AI's sake. The focus is on understanding business problems end to end and determining where large language models, agents, and AI-enabled workflows can materially improve how work gets done.\nWorking as part of a fully functioning engineering team, the Full Stack AI Engineer contributes across the delivery lifecycle, from understanding the problem and shaping the solution through development, deployment, and iteration.\nSuccess in this role means writing high-quality code, learning quickly, contributing effectively within a team, and developing the judgment to build AI-enabled software that creates measurable value for clients and the business.\nDuties and responsibilities, as they align to Ryan’s Key Results\nThis role operates in Ryan’s results-oriented and flexible culture, with a strong emphasis on engineering quality, ownership, and measurable outcomes.\nEngineers are trusted to choose appropriate tools, approaches, and AI-assisted workflows rather than follow heavy development processes. That autonomy is paired with clear accountability for the quality, reliability, and business impact of what they deliver.\nThe role is intended for engineers early in their careers. Success is not measured by years of experience or by knowledge of a particular AI framework. It is measured by strong engineering fundamentals, learning agility, quality of thinking, and the ability to contribute working code to AI-enabled solutions.\nActive mentorship and structured opportunities for growth support continued development in both software engineering and applied AI.\nPeople:\nWorks as part of a cross-functional engineering team to design, build, and improve AI-enabled full-stack software.\nCollaborates effectively with engineers, business professionals, and end users to understand requirements and deliver practical solutions.\nParticipates in client-facing conversations where appropriate, communicating technical concepts clearly to both technical and non-technical stakeholders.\nLearns from more experienced team members and contributes knowledge, ideas, and emerging best practices back into the team.\nUses feedback constructively and demonstrates strong learning agility in a rapidly evolving technical environment.\nClient:\nWorks with business professionals and customers to understand problems, workflows, and opportunities for improvement.\nHelps determine where generative AI or agentic approaches can create meaningful value, rather than applying AI where traditional software would be more appropriate.\nContributes to the end-to-end delivery of AI-enabled applications, including discovery, solution design, development, testing, deployment, and iteration. Builds full-stack applications that may incorporate large language models, agent-based workflows, retrieval, APIs, and other AI capabilities as part of the overall architecture.\nSupports the deployment and adoption of solutions used by real users in business and client environments.\nConsiders the complete enterprise workflow when designing solutions, including users, data, integrations, business rules, human oversight, and failure scenarios.\nValue:\nWrites high-quality, maintainable code that contributes to dependable software used by real users.\nApplies AI where it materially improves a process, user experience, decision, or business outcome.\nThinks critically about when an agentic solution is appropriate and when deterministic software is the better choice.\nContributes to solutions that address real-world problems and generate measurable value for clients and the business.\nIterates on deployed applications based on user feedback, performance, reliability, and adoption.\nBalances speed, scope, and engineering quality to support effective delivery.\nMakes effective use of AI-assisted coding tools while maintaining ownership and understanding of the code produced.\nEducation and Experience:\nBachelor’s or master’s degree in Computer Science, Engineering, AI/ML, or a related technical field, or equivalent relevant experience.\nSuitable for recent graduates and candidates with approximately 0-3 years of professional software engineering experience.\nStrong foundation in software engineering, demonstrated through professional work, internships, university projects, personal projects, open-source contributions, hackathons, or equivalent technical experience.\nEvidence of interest in and hands-on exploration of generative AI, large language models, or agentic systems.\nCommercial generative AI experience is not required.\nAbility to explain technical decisions, trade-offs, and personal contribution to projects in detail.\nStrong interest in understanding how AI can change enterprise workflows and software architecture, rather than simply adding AI features to existing applications.\nComputer Skills:\nWe are largely framework-agnostic. What matters most is strong engineering fundamentals, the ability to learn quickly, and evidence that you can build useful software.\nProficiency in at least one general-purpose programming language, such as Python, TypeScript, or JavaScript.\nExperience building full-stack applications through professional work, internships, academic projects, or independent development.\nStrong understanding of core software engineering concepts, including APIs, databases, Git, testing, debugging, and application architecture.\nFamiliarity with frontend and backend development using technologies such as React, Node/TypeScript, Python/FastAPI, or similar.\nConceptual understanding of cloud platforms such as AWS, Azure, or GCP; hands-on deployment experience is beneficial but not required.\nExposure to generative AI application development, including LLM APIs, agentic workflows, retrieval, vector databases, or agent frameworks such as LangChain, LangGraph, or AutoGen.\nFamiliarity with AI-assisted coding tools such as Claude Code, Codex, or similar, with the ability to validate and understand AI-generated code.\n#Li-hybrid\n#LI-DR1","description_format":"text","description_chars":6827,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule","Gym membership"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services","Tax Advisory & Preparation"],"lifecycle":[{"event":"open","at":"2026-09-26T17:47:25Z"}],"liveness":{"score":66,"band":"ok","label":"Likely open","p_open":1,"p_active":0.736,"p_room":0.9,"age_days":23,"expected_fill_days":40,"reasons":["conf:2","velocity","win:mid","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/ryan-full-stack-ai-engineer","json_url":"https://alion.io/job/ryan-full-stack-ai-engineer.json","meta":{"generated_at":"2026-10-01T11:22:38Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2971,"day_limit":5000,"remaining_today":2029,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}