10 Genai Applications Jobs

Job Title: AI/ML Engineer Experience: 4 To 8 Years Location: Bangalore Key Responsibilities Design, build, and optimize AI/ML solutions for enterprise applications. Develop Generative AI applications with workflows such as RAG Build and deploy AI agents using frameworks like LangGraph, Crew, or PydanticAI . Implement LLM integration and optimize Prompt Engineering workflows (Eg ., GPT, Claude, LLaMA). Collaborate with cross-functional teams to integrate AI solutions into production systems. Utilize Databricks, REST APIs, WebSockets, and event-driven architectures for scalable deployments. Ensure adherence to SDLC best practices, CI/CD pipelines (Jenkins), and Git-based workflows. Leverage AI-augmented development tools for rapid prototyping. Knowledge of enterprise security, compliance, and governance in AI systems. Familiarity with model lifecycle and code management best practices . Required Skills 35 years of experience in Machine Learning/Artificial Intelligent. Experience in Generative AI application development. Strong proficiency in Python and modern software development practices. Hands-on experience with LLMs and prompt engineering . Experience in cloud-native deployment strategies . Strong understanding of agile methodologies and collaborative development . Exposure to MLOps/LLMOps workflows and model monitoring .

Role Overview: You will be responsible for designing, building, and deploying Generative AI models using foundational models like GPT, BERT, LLaMA, PaLM, etc. Additionally, you will develop scalable GenAI applications, integrate them with enterprise systems using APIs and SDKs, and fine-tune large language models (LLMs) for domain-specific use cases. You will also design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure, collaborate with data scientists to productionize ML models, and automate deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools. Furthermore, you will ensure security, compliance, and governance of ML workflows and data, troubleshoot and optimize ML workflows, and document architecture, processes, and operational procedures. Key Responsibilities: - Design, build, and deploy Generative AI models using models like GPT, BERT, LLaMA, PaLM - Develop scalable GenAI applications and integrate with enterprise systems using APIs and SDKs - Fine-tune and optimize large language models (LLMs) for domain-specific use cases - Design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure - Collaborate with data scientists to productionize ML models using best practices in Azure MLOps - Automate the deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools - Implement scalable model training, validation, and deployment workflows in the cloud - Monitor model performance in production, retrain models as needed, and ensure security, compliance, and governance of ML workflows and data - Develop Python scripts and tools to automate tasks, troubleshoot and optimize ML workflows, and document architecture, processes, and operational procedures Qualifications Required: - Hands-on experience with transformer-based models (e.g., GPT, BERT, LLaMA, etc.) - Familiarity with tools like LangChain, LlamaIndex, Haystack, etc. - Experience in prompt engineering, retrieval-augmented generation (RAG), and model fine-tuning - Proven experience in MLOps, specifically with Azure services - Strong programming skills in Python - Experience with Hugging Face Transformers, PyTorch or TensorFlow - REST APIs and/or gRPC for model integration - Experience with Azure Databricks, Azure Machine Learning, Azure OpenAI - Familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch) - Experience building and managing CI/CD pipelines for ML models using Azure DevOps or equivalent tools - Building REST APIs for ML inference using frameworks like FastAPI or Flask - Understanding of containerization technologies like Docker and orchestration using Kubernetes - Knowledge of machine learning lifecycle management, model versioning, and deployment strategies - Experience with data engineering, data pipelines, and ETL processes on Azure - Familiarity with monitoring tools and logging frameworks for production systems - Strong problem-solving skills and ability to work in a collaborative, fast-paced environment,

Job Description Responsibilities: Design, build, and deploy Generative AI models using foundational models like GPT, BERT, LLaMA, PaLM, etc. Develop scalable GenAI applications and integrate with enterprise systems using APIs and SDKs. Fine-tune and optimize large language models (LLMs) for domain-specific use cases. Design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure, leveraging services like Azure Machine Learning, Azure DevOps, and Kubernetes. Collaborate with data scientists to productionize ML models using best practices in Azure MLOps . Automate the deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools. Implement scalable model training, validation, and deployment workflows in the cloud. Monitor model performance in production and retrain models as needed to maintain accuracy and reliability. Ensure security, compliance, and governance of ML workflows and data. Develop Python scripts and tools to automate repetitive tasks and improve operational efficiency. Troubleshoot and optimize ML workflows for performance and cost-effectiveness. Document architecture, processes, and operational procedures. Qualification: Hands-on experience with transformer-based models (e.g., GPT, BERT, LLaMA , etc.) Familiarity with tools like LangChain, LlamaIndex, Haystack, etc. Experience in prompt engineering, retrieval-augmented generation (RAG), and model fine-tuning. Proven experience in MLOps , specifically with Azure services. Strong programming skills in Python Experience with Hugging Face Transformers, PyTorch or TensorFlow. REST APIs and/or gRPC for model integration. Experience with Azure Databricks, Azure Machine Learning, Azure OpenAI Familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch). Experience building and managing CI/CD pipelines for ML models using Azure DevOps or equivalent tools. Building REST APIs for ML inference using frameworks like FastAPI or Flask. Understanding of containerization technologies like Docker and orchestration using Kubernetes. Knowledge of machine learning lifecycle management, model versioning, and deployment strategies. Experience with data engineering, data pipelines, and ETL processes on Azure. Familiarity with monitoring tools and logging frameworks for production systems. Strong problem-solving skills and ability to work in a collaborative, fast-paced environment. Technical Skills: GenAI models: GPT, BERT, LLaMA, PaLM Framework: PyTorch or TensorFlow Cloud Platforms: Microsoft Azure (Azure ML, Azure Databricks, AKS, Azure DevOps) Programming Languages: Python CI/CD Tools: Azure DevOps, GitHub Actions, Jenkins Containerization: Docker, Kubernetes Data Storage & Processing: Azure Blob Storage, Azure SQL, Azure Data Factory Monitoring & Logging: Azure Monitor, Application Insights, Prometheus, Grafana Mandatory skills GPT/BERT/LLaMA, MLOps , Python, Azure Databricks, Azure Machine Learning, Azure OpenAI, GenAI applications, Transformer-based models Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders. Job Description - Grade Specific Has more than a year of relevant work experience. Solid understanding of programming concepts, software design and software development principles. Consistently works to direction with minimal supervision, producing accurate and reliable results. Individuals are expected to be able to work on a range of tasks and problems, demonstrating their ability to apply their skills and knowledge. Organises own time to deliver against tasks set by others with a mid term horizon. Works co-operatively with others to achieve team goals and has a direct and positive impact on project performance and make decisions based on their understanding of the situation, not just the rules.

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS. Architecture & Engineering Specialist - ML Engineering ZS's India Capability & Expertise Center (CEC) houses more than 60% of ZS people across three offices in New Delhi, Pune and Bengaluru. Our teams work with colleagues across North America, Europe and East Asia to create and deliver real world solutions to the clients who drive our business. The CEC maintains standards of analytical, operational and technological excellence across our capability groups. Together, our collective knowledge enables each ZS team to deliver superior results to our clients. ZS's Scaled AI practice is part of ZS's rich and advanced AI ecosystem, in the Architecture & Engineering Expertise Center, focused on creating continuous business value for clients using a range of innovative machine learning, deep learning, and engineering capabilities. Being part of Scaled AI practice allows you to collaborate with data scientists to create state-of-the-art AI models, create and use cutting-edge ML platforms, create and deploy advanced ML pipelines and manage the complete ML lifecycle. What You'll Do Design and implement technical features leveraging best practices for technology stack being used Collaborate with client-facing teams to understand solution context and contribute to technical requirement gathering and analysis Work with technical architects on the team to validate design and implementation approach Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths Uses bug tracking, code review, version control, and other tools to organize and deliver work Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies Consistently contribute in researching & evaluating the latest technologies through rapid learning, conducting proofs-of- concept and creating prototype solutions Support the project architect in designing modules/component of the overall project/product architecture Breaks down large features into estimable tasks lead estimation and can defend them with clients Implement complex features with limited guidance from the engineering lead. For example service or application-wide change Systematically debug code issues/bugs using stack traces, logs, monitoring tools, and other resources Performs code/script reviews of senior engineers in the team Mentor and groom technical talent within the team What You'll Bring At least 5+ relevant hands-on experience in deploying and productionizing ML models at scale Experience in scaling GenAI or similar applications to accommodate a high number of users, large data size, and reduce response time. Strong knowledge in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex Experience in creating GenAI applications such as answering engines, extraction components, and content authoring. Expertise in Designing, configuring, and using ML Engineering platforms like Sagemaker , MLFlow , Kubeflow, or other platforms Big data - Hive, Spark, Hadoop, queuing system like Apache Kafka/Rabbit MQ/AWS Kinesis Ability to quickly adapt to new technology and be innovative in creating solutions Ability to independently run POCs on new technologies and document findings to share Strong in at least one of the Programming languages - PySpark , Python or Java, Scala, etc. and Programming basics - Data Structures Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, ingestion patterns (batch, real-time) Experience in designing and implementation of solution on distributed computing and cloud services platform (but not limited to) - AWS, Azure, GCP Hands-on experience building CI/CD pipelines and awareness of practices for application monitoring Additional Skills: AWS/Azure Solutions Architect certification with an understanding of broader AWS/Azure stack Understanding DevOps CI / CD, data security, experience in designing on cloud platform Willingness to travel to other global offices as needed to work with the client or other internal project teams Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client facing ZSers business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems-the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive. If you're eager to grow, contribute, and bring your unique self to our work, we encourage you to apply. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To complete your application: Candidates must possess or be able to obtain work authorization for their intended country of employment.An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At:

As a Senior Architect AI Products supporting Novartis" Commercial function, you will play a crucial role in driving the architectural strategy that facilitates the seamless integration of data and AI products across various key areas such as omnichannel engagement, customer analytics, field operations, and real-world insights. Your responsibilities will involve collaborating with commercial business domains, data platforms, and AI product teams to design scalable, interoperable, and compliant solutions that enhance the impact of data and advanced analytics on healthcare professional and patient engagement. You will be tasked with defining and implementing the reference architecture for commercial data and AI products, ensuring alignment with enterprise standards and business priorities. Additionally, you will architect the integration of data products with AI products and downstream tools, promoting modular, scalable design to encourage reuse and interoperability across different markets and data domains within the commercial landscape. Stakeholder alignment will be a key aspect of your role, as you will partner with various teams to guide solution design, delivery, and lifecycle evolution. Your role will also involve supporting the full lifecycle of data and AI, including ingestion, transformation, model training, inference, and monitoring within secure and compliant environments. It will be essential to ensure that the architecture complies with governance, data privacy, and commercial requirements while constantly seeking opportunities for architectural improvements, modern technologies, and integration patterns to enhance personalization, omnichannel engagement, segmentation, targeting, and performance analytics. To excel in this position, you are expected to demonstrate proven leadership in cross-functional architecture efforts, possess a good understanding of security, compliance, and privacy regulations in the commercial pharma sector, and have experience with pharmaceutical commercial ecosystems and data. A strong background in data platforms, pipelines, and governance, as well as knowledge of AI/ML architectures supporting commercial use cases, will be advantageous. Additionally, a bachelor's or master's degree in computer science, engineering, data science, or a related field, along with at least 10 years of experience in enterprise or solution architecture, are desirable qualifications for this role. Novartis is committed to diversity, equal opportunity, and inclusion, striving to build diverse teams that represent the patients and communities served. By joining Novartis, you will become part of a community of passionate individuals collaborating to achieve breakthroughs that positively impact patients" lives. If you are ready to contribute to creating a brighter future through innovation and collaboration, we invite you to explore career opportunities at Novartis.,

The role of AI Engineer at our company involves developing essential software features to ensure timely delivery while meeting the company's performance and quality standards. As an AI Engineer, you will be part of our team working on various data science initiatives, ranging from traditional analytics to cutting-edge AI applications. This position provides a great opportunity to gain experience in machine learning and artificial intelligence across different domains. Your core responsibilities will include developing and maintaining data processing pipelines using Python, creating and deploying GenAI applications through APIs and frameworks like semantic kernel and Langchain, conducting data analysis and generating insightful visualizations, collaborating with different teams to understand business requirements and implement AI solutions, contributing to the development and upkeep of language model evaluations and other AI applications, writing clean, documented, and tested code following best practices, and monitoring application performance while making necessary improvements. To qualify for this role, you should hold a Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field, along with at least 2 years of hands-on experience in applied data science and machine learning. Proficiency in Python programming, familiarity with LLMs and their applications, experience with cloud platforms such as AWS, Azure, or GCP, version control using Git, strong analytical and problem-solving skills, and knowledge of PyTorch and Deep Learning fundamentals are essential requirements. In terms of technical skills, you should have knowledge of LLMs and Generative AI platforms, be familiar with popular LLM APIs, have experience with frameworks like Semantic Kernel, LangChain, OpenAI, and Google Vertex AI, be proficient in programming languages including Python, SQL, and R, have expertise in libraries such as HuggingFace, Transformers, Matplotlib, and Seaborn, be skilled in ML/Statistics with tools like scikit-learn, statsmodels, and PyTorch, understand data processing with Pandas, NumPy, and PySpark, and have experience working with cloud platforms like AWS, GCP, or Azure. This full-time permanent position is located in Bengaluru and is with the Merkle brand.,

Join us as a Machine Learning/Artificial Intelligence Engineer, responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences. To be successful as a Machine Learning/Artificial Intelligence Engineer, you should have experience with: - Good years of experience in IT with a background in Development, Machine Learning, and/or Data analysis. - Hands-on experience of NLP/AI/ML tools & technologies GPT, BERT, or other language models. - Experience in building GenAI applications, RAG-based architectures. - Model Development: Research, design, implement, and optimize machine learning models for specific use cases such as predictive analytics, NLP, computer vision, and recommender systems. - Data Preparation: Collect, preprocess, and analyze large datasets to extract meaningful insights and ensure data quality for model training. - Deployment: Build and deploy AI/ML solutions into production environments using appropriate tools and frameworks. - Knowledge of one of the cloud platforms is a must: AWS/AZURE. - Collaboration: Work closely with product managers, data engineers, and software developers to integrate AI capabilities into products and ensure alignment with business objectives. - Performance Monitoring: Evaluate and monitor model performance and accuracy post-deployment, iterating to address challenges and refine models as needed. - Strong Affinity to stay informed on the latest trends, tools, and research in AI and machine learning space. - Support and contribute to data collection efforts, as needed. - Verify data quality to ensure accurate analysis and reporting. - Help identify the business data needed to produce the most useful insights and future analytics. - Utilize data to make actionable recommendations at all levels. - Monitor data management processes to ensure data quality and consistency. - Monitor system performance, data integrity, and usage metrics. - Contribute to data dictionary, standards, training, and ongoing updates. Some other highly valued skills may include: - Web service development experience using REST services/APIs, JSON, XML, IVRs, Jenkins, other Cloud Platforms. - Experience in setting up DevOps pipelines. You may be assessed on the key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology, as well as job-specific technical skills. This role is based in Pune. Purpose of the role: To design, develop, and improve software, utilizing various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities: - Development and delivery of high-quality software solutions by using industry-aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. - Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. - Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. - Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth. - Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. - Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations: - To advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness. Collaborate closely with other functions/business divisions. - Lead a team performing complex tasks, using well-developed professional knowledge and skills to deliver work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives, and determination of reward outcomes. - If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviors to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviors are: L Listen and be authentic, E Energize and inspire, A Align across the enterprise, D Develop others. - OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialization to complete assignments. They will identify new directions for assignments and/or projects, identifying a combination of cross-functional methodologies or practices to meet required outcomes. - Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. - Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. - Take ownership of managing risk and strengthening controls in relation to the work done. - Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organization sub-function. - Collaborate with other areas of work, for business-aligned support areas to keep up to speed with business activity and the business strategy. - Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practices (in other areas, teams, companies, etc.) to solve problems creatively and effectively. - Communicate complex information. "Complex" information could include sensitive information or information that is difficult to communicate because of its content or its audience. - Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

Technical Staff, Software Engineering From applied research to advanced engineering, the CTO Storage team has the expertise to shape ground-breaking Storage products, technologies, and innovations. Its a fascinating field of work. Were involved in assessing the competition, developing Storage technology and product strategies and generating IP. We lead technology investigations, analyze industry capabilities and recommend potential acquisitions or vendor partner opportunities. Our insights influence product architecture and definitions. And we work with colleagues across the business to ensure our products always lead the way. Join us to do the best work of your career and make a profound social impact as a Technical Staff Software Engineer on our CTO Storage Team in Bangalore, India. What youll achieve As a Technical Staff Software Engineering you will be responsible for Storage architecture for data path technologies across our portfolio. You will work with product teams and product management to craft and deliver the best strategy for Dell. You will: Present innovative technical storage ideas at the executive level and develop innovative ideas for Dells storage solutions by keeping abreast of the latest advancements in AI infrastructure, workload orchestration, MLOps platforms, and GenAI applications Architect detailed product designs, specifying functionality, performance, integrations, and hardware requirements Lead prototyping and testing to validate design and functionality, focusing on performance and scalability Refine designs based on feedback, testing, and evolving requirements Work with cross-functional teams, partners, and customers to create POCs and MVPs. Ensure seamless integration of components and technologies Essential Requirements 15+ years of related experience with a bachelors degree; or 12+ years with a masters degree; or 8+ years with a PhD; or equivalent experience Proficiency in AI-driven operations, telemetry systems, and data integration, transformation, and storage connectivity and protocols. Strong experience in designing, developing, and maintaining resilient software infrastructure, and SaaS platforms and Strong experience in development of software systems using C/JAVA/Python Expertise in data migration, replication, synchronization, and familiarity with backup software solutions In-depth knowledge of storage management systems and APIs , including configuration, monitoring, and optimization. Desirable Requirements Possess advanced certifications or have published work in Storage Software Solutions, AI, deep learning, or related fields, with a track record of leading high-impact projects or initiatives in innovative tech domains. Actively contribute to open-source projects or participate in tech communities. Demonstrate a proven ability to mentor and uplift junior team members or peers, with a history of using unconventional thinking to achieve breakthrough solutions. Application closing date: 30 June 2025

Job Title: ML Prompt Engineer Location - Bangalore Hybrid . Job Description: Principle Developer - ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C or C++, AWS Lambda Responsibilities: Responsible for developing, deploying, and maintaining a Retrieval Augmented Generation (RAG) model in Amazon Bedrock, our cloud-based platform for building and scaling generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context, using the Anthropic Claude model as the backbone. Integrate the RAG model with Amazon Bedrock, our platform that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. Optimize the RAG model for performance, scalability, and reliability, using best practices and robust engineering methodologies. Design, test, and optimize prompts to improve performance, accuracy, and alignment of large language models across diverse use cases. Develop and maintain reusable prompt templates, chains, and libraries to support scalable and consistent GenAI applications. Skills/Qualifications: Experience in programming with at least one software language, such as Java, Python, or C/C++. Experience in working with generative AI tools, models, and frameworks, such as Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch, or Jupyter. Experience in working with RAG models or similar architectures, such as RAG, Ragna, or Pinecone. Experience in working with Amazon Bedrock or similar platforms, such as AWS Lambda, Amazon SageMaker, or Amazon Comprehend. Ability to design, iterate, and optimize prompts for various LLM use cases (e.g., summarization, classification, translation, Q&A, and agent workflows). Deep understanding of prompt engineering techniques (zero-shot, few-shot, chain-of-thought, etc.) and their effect on model behavior. Familiarity with prompt evaluation strategies, including manual review, automatic metrics, and A/B testing frameworks. Experience building prompt libraries, reusable templates, and structured prompt workflows for scalable GenAI applications. Ability to debug and refine prompts to improve accuracy, safety, and alignment with business objectives. Awareness of prompt injection risks and experience implementing mitigation strategies. Familiarity with prompt tuning, parameter-efficient fine-tuning (PEFT), and prompt chaining methods. Familiarity with continuous deployment and DevOps tools preferred. Experience with Git preferred Experience working in agile/scrum environments Successful track record interfacing and communicating effectively across cross-functional teams. Good communication, analytical and presentation skills, problem-solving skills and learning attitude

About this role: Wells Fargo is seeking a Software Engineering Senior Manager In this role, you will: Manage, coach, and develop a team or teams of experienced engineers and engineering managers in roles with moderate complexity and risk, responsible for building high quality capabilities with modern technology Ensure adherence to the Banking Platform Architecture, and meeting non-functional requirements with each release Partner with, engage and influence architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation domain architecture and enable application migration paths to target architecture; for example cloud readiness, application modernization, data strategy Function as the technical representative for the product during cross-team collaborative efforts and planning Identify and recommend opportunities for driving escalated resolution of technology roadblocks including code, build and deployment while also managing overall software development cycle and security standards Determine appropriate strategy and actions to act as an escalation partner for scrum masters and the teams to meet moderate to high risk deliverables and help remove impediments, obstacles, and friction while encouraging constant learning, experimentation, and continual improvement Build engineering skills side-by-side in the codebase, conduct peer reviews to evaluate quality and solution alignment to technical direction, and guide design, as needed Interpret, develop and ensure security, stability, and scalability within functions of technology with moderate complexity, as well as identify, manage and mitigate technology and enterprise risk Collaborate with, partner with and influence Product Managers/Product Owners to drive user satisfaction, influence technology requirements and priorities in the product roadmap, promote innovative and intelligent solutions, generate corporate value and articulate technical strategy while being a solid advocate of agile and DevOps practices Interact directly with third party vendors and technology service providers Manage allocation of people and financial resources to ensure commitments are met and align with strategic objectives in technology engineering Hire, build and guide a culture of talent development to have the skills required to effectively design and deliver innovative solutions for product areas and products to meet business objectives and strategy, as well as conduct performance management for engineers and managers Required Qualifications: 6+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 3+ years of management or leadership experience Job Expectations: Manage a team of Software developers, and AI specialists delivering high-impact GenAI solutions. Architect and implement multi-agent orchestration frameworks with strong focus on Agent-Agent-to Communication and connect multi source using Model Context Procol for contextual coordination. Design and Hands-on on implementation of Robust Agentic Engineering frameworks, model validation pipelines, and observability tools for LLM and multi-agent systems. Collaborate with global operation team to build resilient, production-ready AI systems to improve their efficiency Establish and enforce best practices in automated testing, continuous integration, and responsible AI evaluation. Contribute to the architecture and deployment of GenAI applications across cloud-native and on-premises containerized environments. Define OKRs and KPIs for GenAI programs in alignment with strategic business and technology objectives. Promote a culture of engineering excellence and innovation across multidisciplinary teams. Ensure adherence to security, compliance, and ethical Wells Fargo standards in all GenAI deployments. Lead architecture, development, and deployment of GenAI Powered Application and services, ensuring they are enterprise-ready and production-grade. Manage engineering teams building core capabilities such as retrieval-augmented generation (RAG), prompt engineering, multi-agent orchestration, and LLM evaluation pipelines. Partner with AI/ML research, cloud, and security teams to ensure seamless integration of LLM capabilities into business workflows. Establish best practices for LLM observability, responsible AI, testing, and continuous improvement. Collaborate with business stakeholders to translate requirements into scalable AI-powered applications. Promote reusability through reference architectures, shared services, and framework standardization. Contribute hands-on to the design and implementation of core GenAI services, microservices, and data flows. Be Humble: Foster continuous learning and team collaboration. Take Ownership: Embrace accountability and deliver impactful results. Work Transparently: Communicate clearly and build trust across teams. Show Gratitude: Encourage respect, inclusion, and mutual support. Inspire Innovation: Champion new ideas, experimentation, and quality-driven engineering. Additional Required Qualifications: Strong experience in software engineering, including 3+ years in a management or leadership role. 5+ years of experience with Large Language Models (LLMs) and related technologies. 2+ years of experience building and deploying GenAI applications in production. Strong background in Agentic Engineering and AI system design. 5+ years in people management and leadership of technical teams. Professional machine learning certifications from more than one Cloud Providers preferably Azure or Google. Desired Qualifications: Experience with LLM evaluation strategies, prompt engineering, and retrieval-augmented generation (RAG). Experience implementing GenAI observability tools and scalable testing infrastructure. Background in AI governance, responsible AI practices, or enterprise AI quality frameworks. Demonstrated ability to lead QA functions for cutting-edge, research-driven AI applications.