Summary
✨ AI‑Generated
Build and scale production-grade AI-enabled applications using full-stack and cloud-native approaches. You will create reusable patterns for retrieval-augmented generation, document processing, agents and workflows, integrate AI into enterprise systems, and establish evaluation, observability, reliability, and security practices.
Highlights
Build production-grade AI applications and reusable AI frameworks while applying modern cloud-native engineering practices. The role combines hands-on generative AI work, enterprise integration, engineering excellence, and opportunities to enable other teams.
Description
Position: AI Solutions Engineer
Location: NYC, NY (Onsite)
Duration: 12 Months
Interview type: In person required
Note: Need locals or nearby who can go in person for interview
Responsibilities
Build and Scale AI Solutions
1.Design and deliver production‑grade AI‑enabled applications using modern full‑stack and cloud‑native patterns
2.Build reusable AI frameworks and reference implementations (e.g., RAG, document processing, agent/workflow patterns)
3.Integrate AI into enterprise platforms and workflows with strong engineering discipline (clean code, automation, observability, reliability)
Apply AI with an AI‑First Mindset
1.Use AI to accelerate delivery, reduce friction, and scale outcomes
2.Implement applied GenAI patterns including RAG, prompt/tool orchestration, agentic workflows, and evaluation with guardrails
3.Design model‑agnostic solutions resilient to rapid AI ecosystem change
Enable Teams and Own Engineering Excellence
1.Turn complex AI implementations into simple, repeatable patterns
2.Mentor engineers; lead architecture and design reviews to raise quality and consistency
3.Partner with stakeholders on requirements and shippable milestones
4.Own DevOps hygiene (CI/CD, automated testing, telemetry, monitoring) and drive continuous improvement
Required Skills
AI‑first builder mindset, designing reusable solutions for scale and impact, with clear technical communication6+ years building and operating production full‑stack systems at scaleHands‑on experience with distributed, cloud‑native architectures (APIs, data, event‑driven systems)Strong foundation in system design, scalability, resiliency, security, and observabilityHands‑on, production experience building AI/GenAI‑powered applications, not just experimentation or POCsApplied GenAI expertise including RAG, LLM integration/orchestration, prompt design, and evaluation/guardrailsProficiency in Java and/or Python with modern frameworks (e.g., Spring Boot, Python services)Experience with CI/CD, automated testing, and production observability
Desired Skills
Public cloud experience (Azure preferred)Experience building internal platforms, frameworks, or developer toolingFamiliarity with vector databases, embedding, Kafka, or high‑volume messaging systemsExperience in regulated or financial services environmentsExperience working with globally distributed engineering teams
