{"id":1270559,"url":"https://alion.io/job/logiciel-solutions-senior-applied-ai-engineer","title":"Senior- Applied AI Engineer","company":{"id":2191773,"name":"Logiciel Solutions","domain":"logiciel.io","url":"https://alion.io/company/logiciel","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"LLMOps","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false},{"name":"n8n","optional":true},{"name":"Text-to-Speech","optional":true}],"status":"live","first_seen_at":"2025-12-30T00:00:00Z","employer_posted_date":"2025-12-30","last_verified_at":"2026-10-29T06:32:28Z","board_verified":true,"closed_at":null,"days_open":303,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":303},"description":"This is a remote position.\nSenior Applied AI Engineer\nLocation: Onsite / Hybrid\nDepartment: Engineering & Delivery\nRole Type: Full-Time / Senior Individual Contributor\nAbout the Role\nWe are looking for a Senior Applied AI Engineer to design, build, and deliver production-ready AI agents and automation workflows across a variety of client and internal use cases. This is our first dedicated AI engineering hire, responsible for establishing how Logiciel approaches applied AI from early prototypes through to hardened production systems.\nYou will work closely with engineering teams, help shape solution architecture, build demos and proofs of concept where needed, and ultimately deliver reliable, maintainable AI-driven systems. You will also support pre-sales discussions by evaluating feasibility, estimating effort, and guiding what commitments we make.\nThis is an applied engineering role. We want someone who can build, integrate, iterate, and ship.\nWhat You’ll Do / Own\n1. Build Applied AI Agent Systems\nYou will design and implement multi-step agents, reasoning flows, and automation workflows that interact with internal and external systems.\nResponsibilities:\nImplement agent logic, tooling, and workflow orchestration.\n\nDevelop retrieval pipelines and knowledge-grounding workflows.\n\nBuild structured extraction flows using LLMs and transformation logic.\n\nConvert prototypes into production-ready services with monitoring and predictable behaviour.\n\nEnsure agents are explainable, observable, and have well-defined failure and fallback paths.\n\n2. Architect and Integrate End-to-End Solutions\nYou will connect backend services, data sources, and AI components into cohesive systems.\nResponsibilities:\nDefine architecture for applied AI solutions using TypeScript/Node and Python.\n\nIntegrate agents with APIs, databases, event systems, and existing product surfaces. Familiarity with Agent integration protocols like MCP or A2A is expected here as well.\n\nEstablish patterns for prompt management, model selection, retrieval, and verification.\n\nImplement evaluation pipelines to monitor accuracy, drift, and reliability.\n\nBuild reusable modules and internal tooling that accelerate future AI development.\n\n3. Prototypes, Demos and Pre-Sales Support\nYou will help shape early opportunities and ensure we commit to what we can deliver.\nResponsibilities:\nBuild functional prototypes and demos to validate ideas.\n\nAssess feasibility, complexity, and potential risks of proposed AI features.\n\nCollaborate with sales and delivery teams on scope and technical approach.\n\nProvide guidance on trade-offs between different model and architecture choices.\n\nHelp create realistic timelines and delivery plans.\n\n4. Technical Leadership and Mentorship\nYou will uplift Logiciel’s engineering capability in applied AI.\nResponsibilities:\nMentor backend engineers on AI patterns, workflows, and integration techniques.\n\nIntroduce practices for testing, evaluation, observability, and versioning.\n\nShare knowledge on effective prompting, model behaviour, and tool usage.\n\nHelp establish Logiciel’s standards for applied AI solution design and delivery.\n\nWhat Success Looks Like\nAI-driven features and agents are delivered predictably and behave reliably in production.\n\nRetrieval and grounding workflows are well-tuned, observable, and continuously improving.\n\nPrototypes support better decision-making and stronger pre-sales conversations.\n\nEngineering teams understand how to integrate AI components responsibly and effectively.\n\nLogiciel develops a consistent, repeatable approach to applied AI delivery.\n\nSkills and Experience (Non-Negotiable)\n6-9 years of software engineering experience with strong backend fundamentals.\n\nProven experience building and shipping applied AI systems or agents in production.\n\nStrong hands-on experience with TypeScript/Node and Python.\n\nExperience with agent frameworks or custom orchestration patterns.\n\nStrong understanding of retrieval workflows, embeddings, chunking, and evaluation methods.\n\nExperience working with vector databases and related tooling.\n\nDecent understanding of underlying infrastructure and production operations i.e LLMOps\n\nAbility to design and integrate multi-step workflows with external systems and APIs.\n\nComfortable working from prototype to production with attention to reliability and observability.\n\nAbility to break down ambiguous ideas and propose clear, technically grounded solutions.\n\nStrong communication skills, especially when explaining feasibility and technical trade-offs.\n\nNice to Have\nExperience with speech-to-text or text-to-speech pipelines.\n\nFamiliarity with workflow engines or orchestration tools.\n\nExperience with evaluation frameworks or custom benchmarking pipelines.\n\nExposure to model monitoring, versioning, or lightweight MLOps practices.\n\nPrior involvement in pre-sales or client-facing technical discussions.\n\nExperience mentoring engineers on applied AI practices.\n\nExperience with no code tools like n8n `\n\nWho You Are\nA pragmatic engineer who prefers delivering working systems over theoretical research.\n\nComfortable operating in ambiguity and iterating quickly on early concepts.\n\nAble to balance exploratory work with production-grade engineering.\n\nSomeone who thrives in fast-moving environments where people wear multiple hats.\n\nExcited to shape Logiciel’s early applied AI capabilities and engineering foundations.\n\nWhy Join Us?\nBecome the foundational hire for Applied AI at Logiciel.\n\nOwn high-impact projects from design to deployment.\n\nInfluence architecture, patterns, and future team growth.\n\nWork in a culture that values engineering clarity, autonomy, and tangible results.\n\nHow to Apply\nSend your profile to  or reach out directly if you’d like to discuss the role.","description_format":"text","description_chars":5794,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Custom Software Development","AI Consulting & Integration"],"lifecycle":[{"event":"open","at":"2026-09-25T23:55:56Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long 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