Solutions Architect

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 complete engagement from discovery and scoping, through architecture and help build/co-build.

Key job responsibilities
Lead discovery through production rollout for strategic enterprise accounts, co-building and architecting agentic systems on Amazon Bedrock, AgentCore, and Strands Agents
2. Translate requirements into Guardrails, Automated Reasoning Checks, data residency configurations, and audit-ready compliance artifacts that regulated enterprises can take to their risk teams.
3. Design and deliver working AI prototypes, then architect the path to production, hardening with eval frameworks, IaC (AWS CDK), observability, and enterprise security
4. Architect and co-develop production MCP servers, RAG pipelines, multi-agent orchestrations, and LLM-as-judge eval frameworks alongside customer engineering teams, leaving them with complete, owned deployment packages they can operate independently.
5. Codify repeatable deployment patterns into AWS-wide playbooks and feed structured field signal (model gaps, eval results, feature friction) directly to Amazon Bedrock PM and AgentCore engineering teams, shaping the AWS AI roadmap for India.

Basic Qualifications

- 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 delivering products to volume production
- Experience translating customer needs into business requirements
- Experience in customer engagement
- Experience navigating prospective accounts from and into a senior executive level to identify new customer opportunities
- • 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.
- • Architect AI systems for auditability: model version pinning, prompt logging, PII redaction, inference geography (ap-south-1), and compliance artifact generation.
- • Deliver eval-driven acceptance criteria: define benchmark suites, run eval loops against domain-specific test sets, and produce launch-evidence packages that satisfy customer risk / model governance teams.
- • Run structured discovery (jobs-to-be-done, process mining, failure mode analysis) to identify AI leverage points and sequence delivery for maximum early impact.
- 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.

Preferred Qualifications

- Experience working within software development or Internet-related industries

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Experience Level

Senior Level