Solutions Architect
Indexed description
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
- Translate requirements into Guardrails, Automated Reasoning Checks, data residency configurations, and audit-ready compliance artifacts that regulated enterprises can take to their risk teams.
- Design and deliver working AI prototypes, then architect the path to production, hardening with eval frameworks, IaC (AWS CDK), observability, and enterprise security
- 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.
- 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.
- 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.
- Experience working within software development or Internet-related industries
Company - AWS India - Karnataka
Job ID: A10456172
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