Staff Architect - GenAI Job in Amex at Other
- Kpr sugar apperals
- 8 to 12 Yrs
- Other Haryana
- 3 months ago
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Job Description
- You Lead the Way. Weve Got Your Back. With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, youll learn and grow as we help you create a career journey thats unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally. At American Express, youll be recognized for your contributions, leadership, and impactevery colleague has the opportunity to share in the companys success. Together, well win as a team, striving to uphold our company values and powerful backing promise to provide the worlds best customer experience every day. And well do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong. GENAI Staff Architect of Digital Workspace AI/ML Platform What is Amexs objective for a digital workplace The Digital Workplace AI/ML Platform with GENAI capabilities aims to bring together the data from all Unified Workspace, Collaboration and Colleague Servicing platforms, combining this with HR, Information Security, and network data to provide real-time, meaningful insights in areas such as user experience, health scoring, productivity, and overall IT visibility. As the Engineering GENAI Staff Architect of the Digital Workplace AI/ML Platform, you will have responsibility for leading the engineering teams technically to develop the AI/ML and GENAI platform and enhance it to provide personalization capabilities, analytics, and predictive analysis using AI/ML and GENAI. Our winning aspiration is to deliver the best Colleague digital experience. We simplify work and raise productivity by empowering Colleagues with the best digital tools and services. Opportunity for Impact: Digital Workplace at American Express is entering into a new phase of technology transformation driven by opportunities to improve Colleague experience, raise productivity and collaboration, and drive operational efficiency of all service and infrastructure operations. If you have the talent and desire to deliver innovative products and services at a rapid pace, with hands on experience and strategic thinking, in areas of productivity and collaboration software suites, endpoint computing and security, mobile platforms, data management and analytics, and software engineering, join our leadership team to help with our transformation journey. Role and Responsibilities: The AI//ML platform with GENAI capabilities is central to the future of how we work and improve colleague experience while identifying opportunities for improvement. As the leader of this group, you will: Create and manage a complex distributed data engineering pipeline at scale and manage its availability, throughputs, and security. Lead engineering teams and partner with Product Management to enhance the quality and outcomes of the data products including data analytics & visualization Lead the solutioning of AI/ML models on the data to build meaningful insights & predictive analysis Work & collaborate with Product Management and Digital Workplace teams to influence key decisions on architecture and implementation of scalable, reliable, and cost-effective AI/ML platform Bring thought leadership to advance the overall state of technology and customer focus for the platform Introduce AI/ML enterprise architectural paradigms and solutions into the portfolio. Drive both high level and detailed design and conduct design reviews Engage and work with cross-functional leaders to understand and help define business principles, goals and strategy within scope of responsibility. Communicate to senior leaders regarding strategy direction and changes. Mentor engineers and solution architects to ensure technology complexities are understood very clearly to implement solutions expeditiously with high quality Manage delivery milestones, deployment cycles & delivery of the overall AI/ML Platforms roadmap Enthusiasm for staying up-to-date with the latest advancements in AI, NLP, and large language models. A portfolio showcasing previous language model projects, contributions to open-source projects, or relevant publications is a plus. Build, inspire, and grow talented engineering teams that are responsible for designing and building AI and LLM solutions, and Analytics suits Build culture of innovation, ownership, accountability, and customer focus Contribute to the American Express Data Strategy. Working with other Technology teams to drive enterprise architectural solutions, define best practice at a company level and further develop skills and experience outside Digital Workplace. Partner with the Digital Workplace technology teams to develop the AI/ML. platform strategy across all products and channels. Participate actively and constructively in agile team meetings and application reviews Work directly with and learn from the business, product, and engineering leaders across the organization Strengthen the collaboration with Industry partners/suppliers for more robust data solutions and market research for innovative solutions in this space. Professional Qualifications: Demonstrated experience leading engineering teams in remote and distributed product engineering setup. Experience writing software in Python, Scala or similar. Experience with data structures, algorithms, and software design. Exposure to Data Science including Predictive Modelling. Develop Algorithms in multilingual conversational systems. Solve real-world scenarios for user commands and requests by identifying the right LLM models, tooling and frameworks. Strong foundation in machine learning concepts and techniques, including deep learning architectures, natural language processing, and text generation. Demonstrated ability to design, train, fine-tune, and optimize large language models for specific tasks. Familiarity with data augmentation techniques to enhance model performance. Knowledge of LLM operations , including evaluating model performance using appropriate metrics and benchmarks. Ability to iterate and improve models based on evaluation results. Experience in deploying language models in production environments and integrating them into applications, platforms, or services. Exposure in building Predictive models using machine learning through all phases of development, from design through training, evaluation, validation, and implementation. Experience with modern AI/ML & NLP Frameworks (e.g. Tensorflow), Dialogue Managers (e.g.Rasa), Search (e.g. Google Bert, GPT-3), Parsers (e.g. Dialogflow). Extensive experience in designing and implementing large scale cloud-native platforms with high resiliency, availability, and reliability. Strong experience in applications with high throughput and performance. Experience with microservices architectures and service mesh technologies is preferred. Hands on experience in the following environments is preferred: Java, Go, Vert.x, React, Envoy, gRPC, Protobuf, Postgres, CouchBase, Cassandra, Redis, Consul, Jenkins, Docker, Kubernetes, OpenShift, GitHub Actions, Drools, Elastic Stack, Kafka, Spark, ML. Review architecture and provide technical guidance for engineers Experience on various data architectures, latest tools, current and future trends in data engineering space especially Big Data, Streaming and Cloud technologies like GCP, AWS, Azure. Hands on experience with Big Data technologies (Spark, Kafka, Hive, etc.) and have at least 1 Big data implementation on platforms like Cornerstone, Teradata, etc. Experience with Visualization Tools like Tableau, Power BI, etc. Experience with complex, high volume, multi-dimensional data, as well as ML/AI models for unstructured, structured, and streaming datasets. Knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks Exposure in building cloud-native platforms on modern tech stack: AWS, Java, Spring Framework, RESTful API, and container-based application. Ability to learn new tools and paradigms in data engineering and science Proven experience attracting, hiring, retaining, and leading top engineering talent. Creative, passionate, and experienced leader of both technology and guiding teams. IC Tech Architecture savvy (e.g., technical roadmap, system architecture, GENAI platform architecture etc.). Experience with DevOps, reliability engineering, and platform monitoring Well versed in AGILE, DevOps and Program Management methods Bachelors degree with a preference for Computer Science, Masters / Phd is a plus. We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.,
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Employement Type: Full timeIndustry: IT Services & ConsultingRole Category: Not SpecifiedFunctional Area: Not SpecifiedRole/Responsibilies: Staff Architect - GenAI Job in Amex at OtherContact Details:
Company: AmexLocation(s): Other Haryana+ View Contact
Keyskills: Python Scala Data Science Machine Learning Deep Learning Natural Language Processing Predictive Modeling Cloud Computing DevOps Agile Methodology
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