- Principal-level professional with 5+ years of end-to-end ownership of enterprise data architectures on AWS
- C1 English level or higher (written and spoken)
- Deep hands-on expertise across AWS data services, with judgment to select the right tool per use case (object storage, transactional DBs, analytical engines, vector stores).
- Production experience with AWS voice / contact center infrastructure and integrating it into downstream data pipelines.
- Experience evaluating technical decisions on Salesforce migrations (custom objects, APIs, integration patterns, headless approaches).
- Proven experience designing AI grounding and retrieval systems for LLMs in production (RAG, embeddings, retrieval pipelines).
- Experience with multi-model orchestration: sequencing model outputs, preventing data conflicts, coordinating agents.
- AWS cost architecture: reading bills, projecting costs, identifying cheaper alternatives.
- Demonstrated track record of pushing back on vendor or consulting proposals for cloud migrations
Skills
- WS Data Architecture
- S3
- DynamoDB
- Data Lakes
- AWS Bedrock
- Lambda
- Step Functions
- Amazon Connect
- Salesforce Data Architecture
- Salesforce REST API
- Bulk API
- Streaming API
- Bidirectional Data Sync
- RAG Pipelines
- Embedding Strategies
- LLM Retrieval Architecture
- Multi-Model Orchestration
- Agent Orchestration
- AWS Cost Optimization
- Python
- Cloud Migration Architecture
- Serverless Patterns
- AWS Data Architecture
- Bullk API
- Biderectional Data Sync
- Bedrock
- Design the AWS data architecture end-to-end: select the right storage and database approach per use case (object storage, transactional, analytical, vector), and structure data for downstream AI consumption.
- Integrate Salesforce with the AWS data layer: evaluate technical decisions around Salesforce migrations and bidirectional data flows, leveraging existing native services where appropriate.
- Architect voice infrastructure on AWS: design transcription storage and integrate call flow data into the broader data pipeline.
- Define how data is served to AI models: structure, index, and serve data for LLM consumption; design retrieval and grounding strategies appropriate to the problem.
- Design the agent orchestration approach: how agents access data, sequence work, and route exceptions back to human operators.
- Evaluate the AWS migration consulting proposal: identify overengineered components, project post-migration costs, propose alternatives, and represent the client's technical interests against vendor incentives.
- Gather requirements directly from CEO, CTO, and AI/ML lead and translate business processes and data flows into architecture documentation that becomes the foundation for future development.
You will own the complete data and AI architecture for a US-based payment processing and merchant services operation migrating from Salesforce to AWS. This is the most senior technical role on the engagement. You report directly to the CEO, serve as technical counterpart to the CTO, and make architecture decisions with significant infrastructure impact. You will design the AWS data layer, integrate it with the existing Salesforce environment, architect voice infrastructure, and define how data is structured for AI consumption. You will also evaluate vendor proposals from an AWS migration consulting firm and ensure the architecture is cost-efficient and AI-ready.
- AWS Migration Proposal Auditing
- Salesforce Voice Connector
- Snowflake
- AWS Solutions Architect Professional Certification
- AWS Data Analytics Certification
- Payment Processing
- Fintech
- Greenfield AWS Environments