{"id":2485564,"url":"https://alion.io/job/schwab-jobs-senior-python-developer","title":"Senior Python Developer","company":{"id":2930000,"name":"Charles Schwab","domain":"schwabjobs.com","url":"https://alion.io/company/schwabjobs","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":128000,"max_usd":233000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":3287},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"LLM","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Embeddings","optional":true},{"name":"GitHub","optional":true},{"name":"Hugging Face","optional":true},{"name":"IAM","optional":true},{"name":"LangChain","optional":true},{"name":"Machine Learning","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-14T00:14:41Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T19:45:29Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Your Opportunity\nAt Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).\nSchwab Technology Services (STS) enables the future of how clients manage their money by delivering innovative and reliable technology solutions that support investing and financial planning. As GenAI OS Application Developer, you will play a pivotal role in building and advancing Schwab’s Generative AI Operating System (GenAI OS), a cloud-first platform powering intelligent, trusted, and scalable AI-driven solutions across the enterprise.\nIn this role, you will combine hands-on software engineering expertise with technical leadership to deliver production-grade Generative AI applications that drive business value. You will help shape the architecture, development standards, and technical direction of our AI platform while leading a team of engineers through the full software development lifecycle. Working closely with product owners, data scientists, analytics professionals, and technology partners, you will solve complex business challenges by developing scalable cloud-native applications, integrating advanced AI capabilities, and delivering secure, reliable, and observable solutions.\nYou will serve as a key technical leader and agile delivery partner, guiding engineering teams through planning, prioritization, and execution while fostering a culture of innovation, collaboration, accountability, and continuous improvement. This is an exciting opportunity to influence enterprise AI strategy, modernize development practices, and build solutions that help transform how Schwab leverages Generative AI across the organization.\nWhat you have\nRequired Qualifications\nBachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.\n8+ years of experience in software engineering, data science, or AI/ML.\n5+ years of professional software development experience using Python as a primary programming language.\n3+ years of hands-on experience developing and deploying Generative AI applications, including LLM-based solutions, retrieval-augmented generation (RAG), prompt engineering, or GenAI platform capabilities.\n3+ years of experience in technical leadership.\nProven experience building and delivering production-grade cloud-native applications on Google Cloud Platform (GCP), including Cloud Run and containerized services using Docker.\nExperience designing and supporting data orchestration and pipeline solutions using Apache Airflow, Dataflow, or similar technologies.\nExperience developing microservices and RESTful APIs using frameworks such as FastAPI, Flask, or similar technologies.\nExperience working with ReactJS and integrating front-end applications with backend services and APIs.\nStrong understanding of SQL, data modeling, and relational and/or NoSQL database technologies.\nDemonstrated experience leading Agile delivery practices, including sprint planning, backlog management, release planning, prioritization, and daily team coordination.\nExperience driving engineering excellence through code reviews, test-driven development, CI/CD pipelines, and modern software development practices.\nStrong communication, stakeholder management, collaboration, and leadership skills with the ability to influence technical and business decisions across cross-functional teams.\nPreferred Qualifications\nMaster’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline.\nExperience applying AI, machine learning, or Generative AI solutions within financial services or other highly regulated industries.\nDeep knowledge of large language models, transformer architectures, and frameworks such as LangChain, Hugging Face, or similar technologies.\nExperience with vector databases, embeddings, RAG architectures, and AI evaluation or observability frameworks.\nFamiliarity with machine learning frameworks such as PyTorch and TensorFlow, along with MLOps practices and deployment tooling.\nExperience with Infrastructure as Code (IaC), Terraform, DevOps practices, GitHub, and CI/CD automation.\nKnowledge of security, identity and access management (IAM), and compliance considerations in cloud-based environments.\nExperience designing and implementing scalable microservices architectures and object-oriented software solutions.\nExperience building monitoring, observability, and reliability 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