{"id":67293,"url":"https://alion.io/job/fis-systems-operations-engineer-nlp-llm","title":"Senior AI Engineer, Voice & Agentic Systems","company":{"id":4808,"name":"FIS","domain":"fisglobal.com","url":"https://alion.io/company/fis","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":88,"open_postings":102,"ghost_share":0.039,"stale_share":0.51,"repost_share":0.118,"time_to_fill_p50_days":20,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":128000,"max_usd":244000,"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":"A/B Testing","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Fargate","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"DynamoDB","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"OpenSearch","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Terraform","optional":false},{"name":"Text-to-Speech","optional":false},{"name":".NET","optional":true},{"name":"C#","optional":true},{"name":"Java","optional":true},{"name":"LangChain","optional":true},{"name":"Platform Engineering","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-06-22T00:00:00Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-19T03:36:42Z","board_verified":true,"closed_at":null,"days_open":119,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":119},"description":"Job Description\nAbout FIS\nAt FIS, our technology and our people are moving forward. We advance the way the world pays, banks and invests. We believe in building inclusive, diverse teams. Together, we innovate to help our colleagues, clients and communities succeed. If you’re ready to grow your career and make an impact in fintech, we have one question: Are you FIS?\nAbout the Role\nWe are seeking a highly technical Senior AI Engineer to lead the development of our next-generation banking customer experience by building real-time, conversational Agentic AI voice systems from the ground up.\nAbove all else, your primary skill must be an insatiable curiosity to learn, deconstruct, and implement emerging systems. The generative AI landscape evolves weekly, and this role requires a relentless drive to experiment with novel architecture, ingest new research, and translate bleeding-edge concepts into production-grade banking solutions.\nThis role will focus on building production-grade, multi-agent solutions that combine deterministic workflow control with LLM-driven reasoning, real-time speech interaction, secure API integration, and measurable business outcomes.\nThe ideal candidate brings deep software engineering expertise, strong curiosity for emerging AI architectures, and the ability to translate rapidly evolving agentic AI capabilities into reliable, compliant, and scalable financial technology solutions.\nWhat You Will Be Doing\nArchitect and deliver enterprise-scale Agentic voice AI systems that combine deterministic workflow control, LLM-driven reasoning, tool orchestration, memory management, and secure API integration across regulated banking use cases.\n\nBuild production-grade Agentic AI solutions that integrate speech-to-text, text-to-speech, LLMs, cognitive services, and backend enterprise systems to deliver natural, reliable, real-time customer interactions.\n\nDesign agentic workflows that enable AI systems to complete complex, multi-step tasks using structured planning, function calling, tool routing, state management, and human-in-the-loop escalation where appropriate.\n\nOptimize real-time voice interactions for low latency, reliability, scalability, and cost efficiency through streaming architecture, token optimization, semantic caching, prompt tuning, and performance engineering.\n\nDeploy highly available AI services using cloud-native architectures across Azure and AWS, including Kubernetes, container platforms, serverless services, multi-region resilience, and secure DevOps practices.\n\nBuild evaluation, experimentation, and observability frameworks to measure conversational quality, routing accuracy, latency, containment, hallucination risk, tool-call reliability, and production performance.\n\nImplement security, privacy, Responsible AI, and compliance guardrails to protect sensitive customer data and ensure AI systems operate within financial-services regulatory expectations.\n\nTroubleshoot complex issues across distributed AI systems, including network latency, model behavior, prompt failures, token-limit breaches, API errors, orchestration defects, and non-deterministic agent outcomes.\n\nCollaborate with product, architecture, engineering, cloud, data, security, and business teams to translate business requirements into scalable AI solutions.\n\nMentor engineers in AI-first software engineering practices, including reusable component design, automated testing, defensive programming, observability, deployment discipline, and production support.\n\nQualifications & Tech Stack\nRequired Experience & Core Competencies\nEngineering Foundation: 5+ years of backend or platform engineering experience, with strong proficiency in Python, Java, C#, or .NET and a solid foundation in data structures, algorithms, APIs, and distributed systems.\n\nAgentic AI Systems: Hands-on experience designing or building LLM-powered applications, agentic workflows, tool/function calling, state management, retrieval patterns, and multi-step task orchestration.\n\nConversational AI & Voice: Practical experience with conversational AI, speech-to-text, text-to-speech, NLP/NLU, real-time voice interaction patterns, or voice assistant platforms.\n\nProduction AI Delivery: Experience moving AI solutions from prototype to production with attention to latency, reliability, scalability, observability, cost efficiency, and operational resilience.\n\nEvaluation & Quality Engineering: Experience defining evaluation methods for AI systems, including prompt testing, response quality, hallucination risk, tool-call accuracy, routing performance, A/B testing, and regression validation.\n\nCloud & DevOps: Experience deploying services on Azure, AWS, or similar cloud platforms using containers, serverless architecture, CI/CD pipelines, infrastructure as code, and secure configuration practices.\n\nSecurity & Compliance Mindset: Ability to design solutions that protect sensitive data and align with privacy, security, Responsible AI, and regulated-industry expectations.\n\nTroubleshooting & Ownership: Strong debugging, root-cause analysis, and production support skills across complex, asynchronous, distributed, and non-deterministic systems.\n\nLearning Agility: Demonstrated curiosity and ability to rapidly evaluate emerging AI frameworks, models, research patterns, and architecture approaches for practical enterprise use.\n\nRelevant Technology Exposure\nGenerative AI & Model Platforms: Azure OpenAI, Azure AI Foundry, Amazon Bedrock, Amazon SageMaker, OpenAI-compatible APIs, Claude, GPT, or similar commercial and open-source LLMs.\n\nAgentic AI & Orchestration: Microsoft Agent Framework, Microsoft 365 Agents SDK, AutoGen, LangGraph, CrewAI, Amazon Bedrock AgentCore, Durable Functions, Step Functions, or similar workflow orchestration approaches.\n\nVoice & Conversational Platforms: Speech-to-text, text-to-speech, cognitive services, IVR platforms, contact center platforms, voice bots, streaming APIs, and real-time interaction frameworks.\n\nCloud-Native Compute: Azure Kubernetes Service, Amazon ECS/Fargate, Amazon EKS, Azure Functions, AWS Lambda, containers, APIs, and event-driven architectures.\n\nData, Search & Retrieval: Azure AI Search, vector databases, OpenSearch, DynamoDB, graph databases such as Neptune, RAG patterns, semantic search, caching, and structured data integration.\n\nDevOps, Observability & Security: Terraform, CI/CD tooling, Application Insights, CloudWatch, feature flags, identity/access management, secrets management, and production monitoring.\n\nPreferred Qualifications\nExperience delivering AI, cloud, or customer engagement solutions in banking, fintech, or other regulated industries.\n\nExperience with contact center modernization, IVR transformation, CCaaS platforms, or enterprise customer experience systems.\n\nExperience taking emerging AI concepts from research or prototype into reliable, secure, and scalable production implementations.\n\nAdvanced degree in Computer Science, Engineering, Artificial. Intelligence, or a related field, or equivalent practical experience.\n\nWhat We Offer you\n· Opportunities to make an impact in fintech.\n· Personal and professional learning.\n· Inclusive, diverse work environment.\n· Resources to give back to your community.\n· Competitive salary and benefits.\nPrivacy Statement\nFIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.\nEEOC Statement\nFIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here\nFor positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.\nSourcing Model\nRecruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. 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