Generative AI & Machine Learning Engineer
$155,000–$155,000 year
On-siteNew York, United States
Job Summary
Lead end-to-end design, development, and delivery of enterprise AI and machine learning solutions from concept through production deployment. Architect scalable, secure, and resilient AI platforms leveraging Large Language Models, Retrieval-Augmented Generation, and intelligent agents. Provide hands-on technical leadership during solution design, implementation, code reviews, and production support while driving technical planning, estimation, and sprint execution across multiple initiatives. Ensure AI solutions are production-ready with appropriate monitoring, observability, testing, security, and operational support. Drive engineering best practices including CI/CD, automated testing, code quality, infrastructure automation, and MLOps. Mentor engineers and promote engineering excellence through technical guidance, design reviews, and knowledge sharing. Collaborate closely with product owners, business stakeholders, architects, and engineering teams to translate business requirements into high-quality technical solutions.
Required Qualifications
- 10+ years of AI/ML and software engineering experience
- Proven track record of designing, developing, and delivering production-grade AI solutions in enterprise environments
- Proven experience leading engineering teams and delivering complex technology initiatives in large enterprise environments
- Strong hands-on experience developing production-grade AI and machine learning applications
- Deep experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based architectures
- Strong programming skills in Python
- Experience developing distributed systems using microservices, REST APIs, containerization, and cloud-native architectures
- Experience deploying AI applications using modern MLOps and DevOps practices
- Strong understanding of software engineering fundamentals including system design, scalability, resiliency, testing, and performance optimization
- Excellent communication skills with the ability to lead technical discussions across engineering and business teams
- Experience working in Agile software development environments
- Experience with OpenAI, Azure OpenAI, LangChain, LangGraph, or similar AI frameworks
- Experience with vector databases and Retrieval-Augmented Generation (RAG) architectures
- Experience building AI copilots, workflow automation, or agentic AI applications
Desired Qualifications
- Java or another enterprise programming language
- Experience within Investment Banking, Capital Markets, or Financial Services technology
- Experience with Kubernetes, Docker, GitHub Actions, Jenkins, MLflow, or similar DevOps and MLOps tooling
- Familiarity with cloud platforms such as Azure, AWS, or Google Cloud
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