Senior AI Solutions Engineer
Share
Job Location:
New York City, NY - USA
Monthly Salary:
Not Disclosed
Posted on:
3 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Summary Senior AI Solutions Engineer (Morgan Stanley NYC NY)
Position Overview:
- Act as an AI-First Solutions Engineer to accelerate AI adoption across the organization
- Focus on moving AI projects from prototype to production and building reusable frameworks
- Build scalable production-grade AI solutions for enterprise use
- Enable and mentor engineering teams for responsible and effective AI adoption
Key Responsibilities:
- Design and deliver production-ready AI-enabled applications using modern full-stack and cloud-native architectures
- Build reusable AI frameworks reference implementations and starter kits (including RAG agent/workflow patterns)
- Integrate AI into enterprise platforms with strong engineering discipline (clean code automation observability)
- Apply AI to accelerate delivery reduce friction and scale solutions across teams
- Implement GenAI patterns (RAG prompt/tool orchestration agentic workflows) with robust guardrails
- Design model-agnostic solutions resilient to rapid changes in AI ecosystem
- Convert complex AI implementations into simple repeatable patterns for broader adoption
- Mentor engineers and lead architecture/design reviews to improve quality and consistency
- Partner with stakeholders to define requirements and deliver shippable milestones
- Maintain DevOps best practices (CI/CD automated testing telemetry monitoring) and drive continuous improvement
Required Skills:
- 6 years in building and operating production full-stack systems at scale
- Strong hands-on experience with distributed cloud-native architectures (APIs data event-driven systems)
- Strong system design scalability resiliency security and observability skills
- Proven experience building AI/GenAI-powered applications in production (not just POC)
- Applied GenAI expertise: RAG LLM integration prompt design evaluation and guardrails
- Proficiency in Java and/or Python with modern frameworks (Spring Boot Python services)
- Experience with CI/CD automated testing and observability in production environments
- Excellent technical communication and mentoring abilities
Desired Skills:
- Public cloud experience (Azure preferred)
- Experience building internal platforms frameworks or developer tooling
- Familiarity with vector databases embeddings Kafka or high-volume messaging systems
- Experience in regulated or financial services environments
- Experience with globally distributed engineering teams
Success Metrics:
- Number of teams unblocked and enabled
- Speed of AI solutions reaching production
- Breadth of adoption of platforms and frameworks built
Other Requirements:
- Local to NYC or nearby (for in-person interviews)
- US Citizen or Green Card holder
- Valid Drivers License
---
Summary:
This role is for a senior-level AI solutions engineer who will drive scalable and reusable AI adoption at Morgan Stanley by building frameworks mentoring teams and ensuring production-quality engineering practices with a strong focus on GenAI and full-stack cloud-native systems.
Position Overview:
- Act as an AI-First Solutions Engineer to accelerate AI adoption across the organization
- Focus on moving AI projects from prototype to production and building reusable frameworks
- Build scalable production-grade AI solutions for enterprise use
- Enable and mentor engineering teams for responsible and effective AI adoption
Key Responsibilities:
- Design and deliver production-ready AI-enabled applications using modern full-stack and cloud-native architectures
- Build reusable AI frameworks reference implementations and starter kits (including RAG agent/workflow patterns)
- Integrate AI into enterprise platforms with strong engineering discipline (clean code automation observability)
- Apply AI to accelerate delivery reduce friction and scale solutions across teams
- Implement GenAI patterns (RAG prompt/tool orchestration agentic workflows) with robust guardrails
- Design model-agnostic solutions resilient to rapid changes in AI ecosystem
- Convert complex AI implementations into simple repeatable patterns for broader adoption
- Mentor engineers and lead architecture/design reviews to improve quality and consistency
- Partner with stakeholders to define requirements and deliver shippable milestones
- Maintain DevOps best practices (CI/CD automated testing telemetry monitoring) and drive continuous improvement
Required Skills:
- 6 years in building and operating production full-stack systems at scale
- Strong hands-on experience with distributed cloud-native architectures (APIs data event-driven systems)
- Strong system design scalability resiliency security and observability skills
- Proven experience building AI/GenAI-powered applications in production (not just POC)
- Applied GenAI expertise: RAG LLM integration prompt design evaluation and guardrails
- Proficiency in Java and/or Python with modern frameworks (Spring Boot Python services)
- Experience with CI/CD automated testing and observability in production environments
- Excellent technical communication and mentoring abilities
Desired Skills:
- Public cloud experience (Azure preferred)
- Experience building internal platforms frameworks or developer tooling
- Familiarity with vector databases embeddings Kafka or high-volume messaging systems
- Experience in regulated or financial services environments
- Experience with globally distributed engineering teams
Success Metrics:
- Number of teams unblocked and enabled
- Speed of AI solutions reaching production
- Breadth of adoption of platforms and frameworks built
Other Requirements:
- Local to NYC or nearby (for in-person interviews)
- US Citizen or Green Card holder
- Valid Drivers License
---
Summary:
This role is for a senior-level AI solutions engineer who will drive scalable and reusable AI adoption at Morgan Stanley by building frameworks mentoring teams and ensuring production-quality engineering practices with a strong focus on GenAI and full-stack cloud-native systems.
