Solutions Architect

AWS is hiring for Solutions Architects, who embeds directly inside India's most strategic enterprise accounts to architect production AI systems that deliver measurable business impact. The role will support - 4+ years of specific technology domain areas (e. g.

software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience - 2+ years of design, implementation, or consulting in applications and infrastructures experience - 10+ years of IT development or implementation/consulting in the software or Internet industries experience - Experience in industry work in a related environment - Experience in gathering test requirements to create detailed test plans and defining quality metrics to measure product quality - Experience in customer engagement - Experience utilizing AI/ML tools/techniques to develop large scale optimization models -

• Lead discovery workshops with customer CTO / engineering teams to map high-value AI use cases across multiple industry verticals. -

• Own technical scoping, solution architecture for agentic AI workloads on Amazon Bedrock and AgentCore. -

• Build PoCs leveraging Amazon Bedrock, Strands Agents SDK, Amazon AgentCore -

• Design and implement multi-agent orchestrations, MCP tool servers, RAG pipelines (Knowledge Bases for Bedrock, OpenSearch Serverless, Aurora pgvector), and LLM-as-judge evaluation frameworks. -

• Deliver IaC (AWS CDK / CloudFormation / Terraform) for repeatable, production-grade deployment patterns that the customer can own post-engagement. -

• Navigate India's regulatory and translate requirements into Bedrock Guardrails, Automated Reasoning Checks, and data residency configurations. -

• Architect AI systems for auditability: model version pinning, prompt logging, PII redaction, inference geography (ap-south-1), and compliance artifact generation. -

• Build long-term technical relationships with customer engineering leadership and proactively surface new AI deployment opportunities across the account lifecycle. - 4. AWS Field Signal & Product Influence -

• Codify repeatable deployment patterns into AWS-wide playbooks, reference architectures, and GitHub samples that scale insights across hundreds of customers. -

• Feed structured field signal (model gaps, tooling friction, feature requests, eval results) to AWS Engineering teams -

• Collaborate with AWS SA leadership, Specialists, Partner SA, and ISV teams to deliver joint engagements and avoid duplicating effort. -

• Represent AWS AI at customer EBCs, industry conferences, and CXO briefings — you are the technical face of AWS's GenAI capability in the field.