Design end-to-end architectures for Generative AI, agentic AI, enterprise knowledge solutions, document automation, and intelligent workflows while building enterprise-grade data and AI platforms.
Responsibilities
Design end-to-end architectures for Generative AI, agentic AI, enterprise knowledge solutions, document automation, and intelligent workflows.
Define agent architectures covering orchestration, tools, APIs, state and memory management, retrieval, model routing, human-in-the-loop patterns, observability, and failure recovery.
Design enterprise RAG solutions using semantic and hybrid search, vector and graph-based retrieval, metadata filtering, access controls, citations, reranking, evaluation, and feedback loops.
Architect foundation-model integration and model gateway patterns, including model selection, routing, fallback strategies, prompt and context management, safety controls, latency, and cost-performance optimization.
Develop document intelligence and structured-generation patterns for proposals, reports, validation workflows, and engineering artefacts.
Lead go-to-market strategy for AWS databases and AI solutions across North American startups, driving adoption, migrations, and product feedback.
Locations (2)
New York, New York, United States
San Francisco, California, United States
Compensation
USA, CA, San Francisco - 162,700.00 - 220,200.00 USD annually
USA, NY, New York - 162,700.00 - 220,200.00 USD annually
Responsibilities
Own the startup Database and AI GTM strategy across North America, including market sizing, segmentation, sales plays, and revenue and pipeline goals.
Be the database domain authority for startups, leading engagements on engine selection, data modeling, scaling, and cost optimization.
Drive migrations and modernization that move startups off commercial licenses, self managed open source databases, and other clouds onto Aurora, RDS, and DynamoDB.
Drive database attach on GenAI opportunities, including vector search, semantic caching, and agent memory on Aurora PostgreSQL, DynamoDB, ElastiCache, and OpenSearch.
Analyst, Software Engineering focused on data-driven and AI-enabled applications within a regulated financial-services environment.
Responsibilities
Build next-generation AI engineering frameworks, chat agents, and automation capabilities
Develop, test, and maintain Python-based application components, utilities, automation scripts, and data-processing services
Write and optimize SQL queries for data extraction, validation, transformation, reconciliation, and application-support activities
Design, consume, and support REST APIs, including request and response handling, authentication, input validation, error handling, logging, and integration testing
Contribute to AI-enabled application development using AWS Bedrock
Requirements
Bachelor’s degree in Computer Science, Information Technology, Information Systems, Software Engineering, Data Science, or a related field
Build propensity based campaigns and AI powered mechanisms that activate account managers on high potential startups, and measure how many become pipeline and revenue.
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
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