{"schemaVersion":"jobsearcher.job.v1","id":"bfef84d9205a12e58bdb5ecb","url":"https://jobsearcher.com/jobs/bfef84d9205a12e58bdb5ecb","canonicalUrl":"https://jobsearcher.com/jobs/bfef84d9205a12e58bdb5ecb","title":"Data Engineer - Python/AI","description":"Job Description:\r\nAt Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.\r\nBeing a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates' physical, emotional, and financial wellness through affordable, competitive and flexible benefits.\r\nWe value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.\r\nBank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.\r\nAt Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!\r\nJob Description\r\nThis job is responsible for developing and delivering data solutions to accomplish technology and business goals and initiatives. Key responsibilities include performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems. Job expectations include working with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains.\r\nJoin a high-impact technology team within Global Commercial Lending , focused on transforming core lending and payments BAU processes through AI, ML, and Generative AI solutions . This role offers a unique opportunity to design and productionize AI-driven capabilities that deliver measurable efficiency gains , improved operational resilience, and smarter decisioning across large-scale enterprise lending platforms.\r\nYou will work closely with product, operations, and engineering teams to build, deploy, and scale ML and GenAI solutions embedded into mission-critical platforms, while adhering to enterprise standards for security, compliance, and model governance .\r\nThis position is responsible for designing, building, and operating AI/ML solutions end-to-end , with strong emphasis on MLOps, ML lifecycle management, and production readiness .\r\nResponsibilities\r\nWorks across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle\r\nLeverages architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria\r\nBuilds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defines and builds data pipelines and complex data sets to enable data-informed decision making, identifying and raising risks at all stages of the data engineering process\r\nDevelops and executes test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes\r\nDrives complex information technology projects to ensure on-time delivery and adheres to team delivery and release processes\r\nIdentifies, defines, and documents data engineering requirements, communicating required information for deployment, maintenance, support, and business functionality\r\nWorks with technology partners and a diverse set of stakeholders to identify and close gaps in data management standards adherence, negotiates paths forward, and helps identify and communicate solutions to complex data problems leveraging knowledge of information systems, techniques, and processes.\r\nRequired Qualifications\r\nBachelor's degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related: and\r\n6+ years overall experience in software engineering with strong hands-on development in Python\r\n3+ years of hands-on AI/ML experience , building and deploying machine learning models and Gen AI solutions using locally hosted LLMs in production environments\r\nProven experience productionizing ML models using MLflow and enterprise-grade MLOps frameworks\r\nStrong understanding of the end-to-end ML lifecycle : data preparation, feature engineering, training, validation, deployment, monitoring, and retraining\r\nExperience building RESTful APIs and microservices to expose ML capabilities\r\nHands-on experience with CI/CD pipelines , automation, and DevOps practices for ML and application workloads\r\nExperience with containerization and deployment technologies (e.g., Openshift, Docker or equivalent enterprise platforms)\r\nProficiency with version control and enterprise SDLC tools (Git/Bitbucket, Jenkins, pytest, SonarQube, Artifactory, etc.)\r\nExperience working in large, multi-team enterprise environments with shared codebases and governance standards\r\nStrong analytical, problem-solving, and communication skills with ability to engage business and technical stakeholders\r\nDesired Qualifications\r\nExperience applying GenAI / LLM-based solutions (e.g., RAG, summarization, intelligent extraction) to operational and financial services use cases\r\nExposure to model governance, risk management, and compliance controls in regulated environments\r\nExperience building reusable AI frameworks, utilities, or platforms that can be leveraged across multiple teams\r\nFamiliarity with databases, caches, and messaging platforms (e.g., Oracle, MongoDB, Redis, event-driven architectures)\r\nExperience with cloud or hybrid enterprise AI platforms and observability tools\r\nSkills\r\nAnalytical Thinking\r\nApplication Development\r\nData Management\r\nDevOps Practices\r\nSolution Design\r\nAgile Practices\r\nCollaboration\r\nDecision Making\r\nRisk Management\r\nTest Engineering\r\nArchitecture\r\nBusiness Acumen\r\nData Quality Management\r\nFinancial Management\r\nSolution Delivery Process\r\nMinimum Education Requirement: Bachelor's degree or equivalent work experience.\r\nShift\r\n1st shift (United States of America)\r\nHours Per Week\r\n40\r\nJ-18808-Ljbffr","company":"Socket","rawCompany":"socket","city":"Charlotte","state":"NC","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:49:38.009Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"522110","title":"Commercial Banking","slug":"commercial-banking"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer - Python/AI","description":"Job Description:\r\nAt Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.\r\nBeing a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates' physical, emotional, and financial wellness through affordable, competitive and flexible benefits.\r\nWe value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.\r\nBank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.\r\nAt Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!\r\nJob Description\r\nThis job is responsible for developing and delivering data solutions to accomplish technology and business goals and initiatives. Key responsibilities include performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems. Job expectations include working with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains.\r\nJoin a high-impact technology team within Global Commercial Lending , focused on transforming core lending and payments BAU processes through AI, ML, and Generative AI solutions . This role offers a unique opportunity to design and productionize AI-driven capabilities that deliver measurable efficiency gains , improved operational resilience, and smarter decisioning across large-scale enterprise lending platforms.\r\nYou will work closely with product, operations, and engineering teams to build, deploy, and scale ML and GenAI solutions embedded into mission-critical platforms, while adhering to enterprise standards for security, compliance, and model governance .\r\nThis position is responsible for designing, building, and operating AI/ML solutions end-to-end , with strong emphasis on MLOps, ML lifecycle management, and production readiness .\r\nResponsibilities\r\nWorks across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle\r\nLeverages architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria\r\nBuilds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defines and builds data pipelines and complex data sets to enable data-informed decision making, identifying and raising risks at all stages of the data engineering process\r\nDevelops and executes test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes\r\nDrives complex information technology projects to ensure on-time delivery and adheres to team delivery and release processes\r\nIdentifies, defines, and documents data engineering requirements, communicating required information for deployment, maintenance, support, and business functionality\r\nWorks with technology partners and a diverse set of stakeholders to identify and close gaps in data management standards adherence, negotiates paths forward, and helps identify and communicate solutions to complex data problems leveraging knowledge of information systems, techniques, and processes.\r\nRequired Qualifications\r\nBachelor's degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related: and\r\n6+ years overall experience in software engineering with strong hands-on development in Python\r\n3+ years of hands-on AI/ML experience , building and deploying machine learning models and Gen AI solutions using locally hosted LLMs in production environments\r\nProven experience productionizing ML models using MLflow and enterprise-grade MLOps frameworks\r\nStrong understanding of the end-to-end ML lifecycle : data preparation, feature engineering, training, validation, deployment, monitoring, and retraining\r\nExperience building RESTful APIs and microservices to expose ML capabilities\r\nHands-on experience with CI/CD pipelines , automation, and DevOps practices for ML and application workloads\r\nExperience with containerization and deployment technologies (e.g., Openshift, Docker or equivalent enterprise platforms)\r\nProficiency with version control and enterprise SDLC tools (Git/Bitbucket, Jenkins, pytest, SonarQube, Artifactory, etc.)\r\nExperience working in large, multi-team enterprise environments with shared codebases and governance standards\r\nStrong analytical, problem-solving, and communication skills with ability to engage business and technical stakeholders\r\nDesired Qualifications\r\nExperience applying GenAI / LLM-based solutions (e.g., RAG, summarization, intelligent extraction) to operational and financial services use cases\r\nExposure to model governance, risk management, and compliance controls in regulated environments\r\nExperience building reusable AI frameworks, utilities, or platforms that can be leveraged across multiple teams\r\nFamiliarity with databases, caches, and messaging platforms (e.g., Oracle, MongoDB, Redis, event-driven architectures)\r\nExperience with cloud or hybrid enterprise AI platforms and observability tools\r\nSkills\r\nAnalytical Thinking\r\nApplication Development\r\nData Management\r\nDevOps Practices\r\nSolution Design\r\nAgile Practices\r\nCollaboration\r\nDecision Making\r\nRisk Management\r\nTest Engineering\r\nArchitecture\r\nBusiness Acumen\r\nData Quality Management\r\nFinancial Management\r\nSolution Delivery Process\r\nMinimum Education Requirement: Bachelor's degree or equivalent work experience.\r\nShift\r\n1st shift (United States of America)\r\nHours Per Week\r\n40\r\nJ-18808-Ljbffr","datePosted":"2026-08-08T01:49:38.009Z","dateModified":"2026-08-08T01:49:38.009Z","hiringOrganization":{"@type":"Organization","name":"Socket","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Charlotte","addressRegion":"NC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bfef84d9205a12e58bdb5ecb"},"url":"https://jobsearcher.com/jobs/bfef84d9205a12e58bdb5ecb"}}