E
AI Engineer Consultant
Eleven Recruiting
3 hours ago
Full-time
On-site
East New York, New York, United States
About Eleven Recruiting
We are a specialized technology staffing agency supporting professional and financial services companies. Why do we stand out in technology staffing? We listen and act as advisors for our candidates on how they can best add value, find interesting projects, and pave a path for career advancement. We advocate for the best pay, diversity in tech, and the best job fit for every candidate we place.
Our client, a growing SaaS company, is seeking a fully remote Staff AI Engineer to join their team.
Design and build the most technically demanding parts of the system yourself, working in an AI native, agentic coding workflow as your daily practice, not just directing others. Build production-grade pipelines that extract, classify, and validate structured documents across a wide range of formats and quality levels, and define the validation layer that turns raw extraction into output the business can trust. Build the measurement backbone for the platform: task completion rates, accuracy attribution, cost tracking, and regression detection, so that "is this good enough to ship" is backed by data, not opinion. Design the supervision layers, validation rules, human review gates, and audit trail needed to make non-deterministic AI output trustworthy for professionals who can't tolerate errors. Mentor engineers, raise the bar in design and code review, and help spread an AI native, agentic engineering culture across the broader team, reducing key-person risk by leaving systems more legible than you found them.
8+ years building and operating backend systems in production environments where uptime and correctness are critical. ~ A track record of leading the design of complex, distributed, or high-scale systems from architecture through deployment and ongoing operations. ~ You need to have shipped this class of system, not just studied it. ~ Strong experience with relational databases (PostgreSQL or similar): schema design, query optimization, data modeling, and migrations. ~ Hands-on work with event-driven architectures: message queues, async processing, and distributed job execution. ~ Production experience with AWS (Lambda, SQS, S3, ECS) or an equivalent cloud platform. ~ Comfort reading and writing both TypeScript and Python, or clear evidence of picking up a second language quickly. ~ Experience across the full software delivery lifecycle: design, implementation, testing, deployment, monitoring, and incident response. ~ Familiarity with modern agent/LLM tooling such as LangChain, vector databases, and cloud-based model platforms (e.g., AWS Bedrock).
Depth in multi-agent coordination specifically: designing supervision, routing, and hand-off between cooperating agents. Familiarity with RAG architectures, vector databases, or document processing pipelines. Experience with multi-tenant SaaS architecture: schema isolation, tenant-scoped data, and access control. Background in document intelligence: OCR, structured extraction from PDFs, and form understanding. Experience standing up evaluation, observability, or quality systems for ML/LLM products. Work in a regulated or high-trust domain (finance, legal, healthcare, tax) where output correctness is non-negotiable. Open-source contributions, technical writing, or other public evidence of engineering depth.
Legitimate Eleven recruiters will never ask for money, fees, or banking information before your first day.
We are a specialized technology staffing agency supporting professional and financial services companies. Why do we stand out in technology staffing? We listen and act as advisors for our candidates on how they can best add value, find interesting projects, and pave a path for career advancement. We advocate for the best pay, diversity in tech, and the best job fit for every candidate we place.
Our client, a growing SaaS company, is seeking a fully remote Staff AI Engineer to join their team.
Design and build the most technically demanding parts of the system yourself, working in an AI native, agentic coding workflow as your daily practice, not just directing others. Build production-grade pipelines that extract, classify, and validate structured documents across a wide range of formats and quality levels, and define the validation layer that turns raw extraction into output the business can trust. Build the measurement backbone for the platform: task completion rates, accuracy attribution, cost tracking, and regression detection, so that "is this good enough to ship" is backed by data, not opinion. Design the supervision layers, validation rules, human review gates, and audit trail needed to make non-deterministic AI output trustworthy for professionals who can't tolerate errors. Mentor engineers, raise the bar in design and code review, and help spread an AI native, agentic engineering culture across the broader team, reducing key-person risk by leaving systems more legible than you found them.
8+ years building and operating backend systems in production environments where uptime and correctness are critical. ~ A track record of leading the design of complex, distributed, or high-scale systems from architecture through deployment and ongoing operations. ~ You need to have shipped this class of system, not just studied it. ~ Strong experience with relational databases (PostgreSQL or similar): schema design, query optimization, data modeling, and migrations. ~ Hands-on work with event-driven architectures: message queues, async processing, and distributed job execution. ~ Production experience with AWS (Lambda, SQS, S3, ECS) or an equivalent cloud platform. ~ Comfort reading and writing both TypeScript and Python, or clear evidence of picking up a second language quickly. ~ Experience across the full software delivery lifecycle: design, implementation, testing, deployment, monitoring, and incident response. ~ Familiarity with modern agent/LLM tooling such as LangChain, vector databases, and cloud-based model platforms (e.g., AWS Bedrock).
Depth in multi-agent coordination specifically: designing supervision, routing, and hand-off between cooperating agents. Familiarity with RAG architectures, vector databases, or document processing pipelines. Experience with multi-tenant SaaS architecture: schema isolation, tenant-scoped data, and access control. Background in document intelligence: OCR, structured extraction from PDFs, and form understanding. Experience standing up evaluation, observability, or quality systems for ML/LLM products. Work in a regulated or high-trust domain (finance, legal, healthcare, tax) where output correctness is non-negotiable. Open-source contributions, technical writing, or other public evidence of engineering depth.
Legitimate Eleven recruiters will never ask for money, fees, or banking information before your first day.