Solution Architect - FSI, FSI SA

Job description

from Amazon careers

AWS Global Sales (AGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

AWS India is looking for an experienced Solutions Architect to help advise our Financial Services & Insurance (FSI) customers in India on how to best adopt and leverage the value of AWS technology. This is an ideal role for someone with deep experience in the FSI industry, expert knowledge of financial services applications and infrastructure and a solid understanding of the transformational value cloud technologies & GenAI can bring.

In this role, you will engage with customers in India to determine business needs, identify opportunities and issues, and develop related technical solutions and value propositions leveraging the power of AWS cloud technology.

Key job responsibilities
Design customer solutions with a focus on the Financial Services industry, collaborating with the AWS Business Development function and internal teams in India to help customers migrate to AWS cloud-based & GenAI technology solutions.
Architect solutions leveraging AWS technology, including solution development and potentially demonstrate technical feasibility through mechanisms including proof-of-concepts and/or prototypes.
Serve as a thought leadership, evangelizing AWS services and technologies through forums such as AWS blogs, whitepapers, reference architectures and public-speaking opportunities such as AWS first-party events and third-party industry events.
Capture and share best practices and insights internally and with Partners and customers in India.
Identifying customer requirements and providing feedback into appropriate AWS services teams. Provide updates on customer progress and ensure plan execution by partners.
The right individual will leverage FSI Industry expertise, architecture experience, and customer-facing skills to be a "trusted advisor" to customers. They will be able to facilitate relationships with senior executive stakeholders, as well as easily interact with and give guidance to technology experts, software developers, IT professionals, and system architects to ensure better CX and compliance with global AWS standards, practices and policies.
The right individual will also have a demonstrated ability to think strategically about business, product, and technical challenges. If you are someone who enjoys innovating, likes solving hard problems and working on cutting edge technology, we would love to hear from you.

Basic Qualifications

- 7+ years of design, implementation, or consulting in applications and infrastructures experience
- Experience communicating complex ideas to technical and non-technical audiences
- Experience leading engineering discussions around technology decisions and strategy related to a product
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- Hands-on experience with AWS ecosystems (including Bedrock, AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic search optimization

Preferred Qualifications

- Experience working within software development or Internet-related industries
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience (non-internship) in professional software development
- Cloud Technology Certification, or AWS Professional level certification
- Master's degree or above in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Agentic AI expertise - Hands-on experience with multi-agent orchestration, tool use, memory, and guardrails using frameworks such as LangGraph, AutoGen, or AWS AgentCore; proficiency in responsible AI tooling including AWS Clarify, Guardrails for Bedrock, model explainability, and bias detection
- Expertise in architecting AI systems within highly regulated or security-sensitive environments

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