{"id":2617771,"url":"https://alion.io/job/kaleidoscope-innovation-ai-engineer-2","title":"AI Engineer","company":{"id":4382008,"name":"Kaleidoscope Innovation","domain":"kascope.com","url":"https://alion.io/company/kaleidoscope-innovation","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"ADP","truth_index":{"grade":"B","score":75,"open_postings":38,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Charlotte, United 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Teaming","optional":false},{"name":"Redis","optional":false},{"name":"TypeScript","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-06-02T19:59:00Z","employer_posted_date":"2026-06-02","last_verified_at":"2026-10-24T14:38:28Z","board_verified":true,"closed_at":null,"days_open":143,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":143},"description":"We are unable to sponsor or take over sponsorship of an employment visa at this time.\nJob Specs - AI Engineering Lead\nAbout this role\n Wells fFargo is seeking a AI engineering Lead in CIB\nIn This role you will\n· Lead end-to-end design and development of AI systems including chatbots, Retrieval Augmented Generation (RAG) platforms, autonomous agents, and workflow automation tools.\n· Drive complex, multi-domain AI initiatives, ensuring technical excellence across backend services, front-end experiences, and AI model integrations.\n· Architect scalable and secure, AI solutions leveraging Google, OpenAI, Anthropic, Vertex AI, and GitHub’s AI ecosystem.\n· Oversee enterprise-grade deployment pipelines using OpenShift (OCP), Kubernetes, and robust CI/CD patterns to ensure reliable production delivery.\n· Establish engineering best practices across Python, TypeScript, and React for modern, AI-enabled applications.\n· Guide prompt engineering, skill engineering, and model evaluation approaches including guardrails, observability, red teaming, and hallucination detection.\n· Lead and mentor engineering pods , providing technical direction, career development, and architectural guidance.\n· Ensure systems are fully observable, monitored, and resilient, integrating fallback logic and safety controls to mitigate model and system failures.\n· Partner closely with UI/UX, platform, cybersecurity, and governance teams to deliver compliant, user-centric, and secure AI solutions at enterprise scale.\n· Collaborate with business stakeholders and product owners to align AI capabilities with strategic outcomes and define delivery roadmaps.\n· Ensure compliance with cybersecurity, data privacy, and model risk management standards required in regulated financial-services environments.\n· Resolve complex technical issues, escalating and troubleshooting challenges across AI pipelines, backend services, front-end apps, and infrastructure.\n· Lead Agile delivery processes, driving sprint execution, backlog prioritization, risk mitigation, and cross-team coordination.\n· Be well versed in emerging AI technologies, staying current with LLM advancements, evaluation techniques, vector search, and responsible AI practices.\n· Collaborateand influence across all levels, including senior managers, platform teams, and cross-functional partners to advance the AI engineering strategy.\nRequired Qualifications:\n10+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education\nExpert-level proficiency in: Python (AI/ML, backend, orchestration)\nTypeScript and modern React frameworks\n\nExperience building solutions using:OpenAI, Anthropic, Google (Vertex AI), GitHub Copilot / GitHub ecosystem\n\nHands-on experience deploying applications using:OCP/OpenShift, , Kubernetes, CI/CD pipelines\n\nProven ability to lead multiple engineering pods and mentor engineers across levels.\nComfortable executing Agile methodologies across short sprint cycles.\nStrong understanding of:Cybersecurity controls\nModel risk management\nCompliance requirements in regulated financial-services environments\n\nDesired Qualifications:\nExperience building high-availability banking or financial applications.\nFamiliarity with vector databases, embeddings, search systems (e.g., ChromaDB,, Elasticsearch, Redis Vector).\nUnderstanding of evaluation frameworks for LLM outputs (hallucination detection, guardrails, red-teaming).\nExposure to MLOps fundamentals and responsible AI concepts.\nJob Expectations:\nKey Responsibilities\nTechnical Leadership\nLead end-to-end design and implementation of AI systems including chatbots, Retrieval-Augmented Generation (RAG), autonomous agents, and workflow automation tools.\nArchitect scalable, secure solutions leveraging industry-leading AI providers (OpenAI, Anthropic, Google Vertex AI, GitHub Copilot).\nOversee production deployment pipelines using OCP (OpenShift Container Platform) for containerization, orchestration, and runtime operations.\nDefine best practices for Python, TypeScript, and React development within AI-enabled applications.\nProject Delivery & Team Management\nManage and mentor pod teams (approx. 4 / 6 engineers each), ensuring high-quality execution and technical rigor.\nDrive delivery roadmaps, project sequencing, and risk mitigation across multiple concurrent AI initiatives.\nPartner with UI/UX designers to build intuitive, compliant, and enterprise-ready user experiences.\nGuide prompt engineering, skill engineering, and evaluation frameworks for AI model tuning and safety.\nOperational Excellence\nEnsure all AI deployments meet enterprise security, data privacy, and regulatory compliance standards required in Corporate & Investment Banking.\nCollaborate with cybersecurity, risk, and governance teams to enforce secure coding, model-handling, and data-access patterns.\nDesign robust observability, monitoring, and fallback strategies for AI-driven production systems.\nCollaboration & Stakeholder Engagement\nWork closely with product owners, business stakeholders, and platform teams to align AI capabilities with business outcomes.\nCommunicate feasibility, architectural trade-offs, delivery timelines, and technical risks.\nStay current with industry trends, emerging AI technologies, model evaluation techniques, and AI governance standards.\nKaleidoscope, an Infosys Company, is an equal opportunity employer, and all qualified applicants will 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