Solution Architect (DFS)

Key Responsibilities:

• Architect and govern Generative AI and agentic AI solutions using Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Guardrails, and Bedrock AgentCore Runtime, Gateway, Memory, Identity, Evaluations, and Observability.

• Define enterprise standards for end-to-end implementation from requirements and data preparation through evaluation, deployment, and production support.

• Translate business requirements into solution designs, technical plans, delivery estimates, and measurable acceptance criteria.

• Build secure integrations with enterprise applications, APIs, data platforms, and operational workflows.

• Establish evaluation, monitoring, tracing, cost, latency, safety, and reliability controls for production solutions.

• Provide technical direction for reusable components, development standards, documentation, testing, CI/CD, and release governance.

• Lead architecture reviews, stakeholder workshops, framework selection, governance decisions, and technical mentoring across teams.

• Extensive architecture and delivery experience with Amazon Bedrock and Models: Amazon Bedrock, Converse API, Amazon Nova, Anthropic Claude, cross-Region inference profiles.

• Extensive architecture and delivery experience with Bedrock AgentCore: Amazon Bedrock AgentCore Runtime, Harness, Memory, Gateway, Identity.

• Extensive architecture and delivery experience with RAG and Knowledge Bases: Amazon Bedrock Knowledge Bases, Amazon S3, Amazon OpenSearch Serverless, Amazon Aurora, Amazon Neptune Analytics.

• Extensive architecture and delivery experience with Agents and Orchestration: Agents for Amazon Bedrock, AWS Lambda, LangGraph, LangChain, Strands Agents.

• Extensive architecture and delivery experience with Prompt Engineering and Evaluation: Amazon Bedrock prompt management, Bedrock evaluations, Bedrock Guardrails.

• Extensive architecture and delivery experience with Security and Responsible AI: AWS IAM, AWS KMS, AWS Secrets Manager, Amazon Cognito, Amazon VPC.

• Working knowledge of Deployment, LLMOps and Observability, including Amazon CloudWatch, AWS X-Ray, AWS CloudTrail, Amazon ECR.

• Working knowledge of Data and Multimodal AI, including Amazon S3, AWS Glue, AWS Lake Formation, Amazon Athena.

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.

• 13+ years of overall IT experience, including at least 3 years in AI/ML and production Generative AI architecture.

• Strong understanding of LLMs, RAG, agentic automation, prompt engineering, evaluation, and production AI operations.

• Ability to design secure and reliable APIs, tool integrations, data flows, identity controls, and failure-handling mechanisms.

• Experience implementing automated testing, version control, deployment pipelines, monitoring, and rollback practices.

• Good understanding of Responsible AI, privacy, safety, compliance, and enterprise security standards.

• Proven experience leading complex AI/ML initiatives and resolving cross-team technical dependencies.

• Demonstrated ability to mentor engineers, review designs, and improve engineering quality and delivery predictability.

• Demonstrated enterprise architecture experience covering scalability, resilience, security, governance, data boundaries, and platform operating models.

• Ability to evaluate platforms and frameworks using measurable criteria and communicate architectural trade-offs to senior stakeholders.