AmazonPosted 3mo ago

Solutions Architect

Solutions Architect at Amazon scores 76 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

IN, KA, Bengalurufull-time

AI in this role

bedrockpgvector

rag

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 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.

Preferred qualifications

- Experience working within software development or Internet-related industries

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagBedrockpgvector

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through how you've used Bedrock in your day-to-day work.
What are the limits of pgvector that you've run into, and how did you work around them?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: Rag, Bedrock, and pgvector. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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