{"id":2182036,"url":"https://alion.io/job/fis-artificial-intelligence-machine-learning-lead-engineer","title":"Artificial Intelligence / Machine Learning Lead Engineer","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":78,"ghost_share":0.038,"stale_share":0.526,"repost_share":0.115,"time_to_fill_p50_days":20,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":31},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Keras","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorFlow","optional":false},{"name":"Tool Use","optional":false},{"name":"AutoGen","optional":true},{"name":"CI/CD","optional":true},{"name":"Fine-tuning","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"OpenAI","optional":true}],"status":"live","first_seen_at":"2026-10-09T15:12:54Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-12T16:52:04Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Every day at FIS, innovators, problem solvers and changemakers work together to create technology that advances the world of finance. We embrace new ideas, challenge what's possible and empower our teams to make a lasting impact. If you're ready to help shape the future of fintech, unlock your next chapter with FIS.\nAbout the role\nAs an Artificial Intelligence and Machine Learning Engineer Lead, you will design and develop generative artificial intelligence and agent-based solutions across FIS. You will build scalable applications using large language models and integrate them with enterprise platforms, application programming interfaces and workflows. You will also evaluate these systems for accuracy, reliability, safety and effective grounding.\nYour key responsibilities\nDesign and build generative artificial intelligence applications using proprietary and open-weight large language models. \nDevelop agent-based systems and workflows that support planning, memory, tool use, orchestration, human oversight and autonomous tasks. \nIntegrate artificial intelligence solutions with enterprise platforms, application programming interfaces and business workflows. \nBuild and deploy representational state transfer services using Flask or FastAPI. \nEvaluate model, agent and system performance, including accuracy, reliability, grounding and safety. \nWhat you bring\nRequired qualifications\nAt least 10 years of overall professional experience, including at least four years working with artificial intelligence, generative artificial intelligence or agent-based artificial intelligence. \nHands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation. \nStrong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas. \nExperience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI. \nBachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience. \nPreferred qualifications\nExperience fine-tuning large language models, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation. \nFamiliarity with orchestration tools such as LangChain, LlamaIndex, AutoGen or the OpenAI Assistants application programming interface. \nKnowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance. \nThe impact you'll make\nThe FIS artificial intelligence and machine learning team identifies, explores and implements solutions designed to support revenue growth and operational savings. The team brings together solution architects, data scientists and machine learning engineers. As an Artificial Intelligence and Machine Learning Engineer Lead, you will help turn emerging technologies into practical solutions that can be applied across the organization.\nWhat we offer you\nAt FIS, your career journey is yours to shape. We provide the tools, experiences and support to help you reach what's next.\nHere's what else we offer:\nOpportunities to make an impact in fintech \nInternal career growth opportunities \nPersonal and professional learning \nInclusive, diverse work environment \nResources to give back to your community \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.\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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