Senior Developer - AI Software Engineer

Neuberger Berman•New York, NY

2d•$130,000 - $170,000•Hybrid

About The Position

We are seeking a talented Mid-Level AI Software Engineer to join our growing Private Markets AI team. In this role, you will design, develop, and deploy AI-powered capabilities that drive real business impact. You will work closely with business stakeholders, engineering, and data engineering teams to build scalable, production-grade AI systems. This is an exciting opportunity to shape the next generation of intelligent products while growing your expertise in a collaborative and innovative environment.

Requirements

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field
7+ years of professional software development experience, with 2+ years focused on building and deploying AI solutions in production environments
Experience in Private Markets or a related financial sector
Strong proficiency in Python and AI/agentic frameworks, including LangChain and LangGraph
Proven ability to design, build, and architect production-grade agentic workflows and enterprise AI systems using LLMs
Hands-on experience with cloud platforms (AWS or Azure), including native AI services such as Azure AI Foundry, AWS Bedrock, and MCP
Solid software engineering fundamentals — version control (Git), CI/CD, testing, and containerization (Docker)
Strong problem-solving skills with the ability to translate ambiguous business requirements into scalable technical solutions
Experience with prompt engineering and retrieval-augmented generation (RAG)

Nice To Haves

Experience with fine-tuning techniques (LoRA, RLHF)
Familiarity with vector databases (Pinecone, Weaviate, Chroma) and embedding-based search systems
Experience building real-time inference systems or streaming AI pipelines

Responsibilities

Evaluate, design and, architect AI Tooling for production use cases within the Private Markets business solving real-world business problems
Build and maintain end-to-end AI powered solutions covering data ingestion, feature engineering, model training, evaluation, and deployment.
Integrate large language models (LLMs) and foundation models into product features, including prompt engineering, fine-tuning, and RAG architectures.
Partner with the Private markets business users to design and build agentic workflows
Collaborate with data engineers to ensure high-quality, well-structured training datasets and feature stores.
Write clean, well-tested, and well-documented code following engineering best practices.
Participate in code reviews, design discussions, and knowledge-sharing sessions with the broader engineering team.
Stay current with advances in AI/ML research and evaluate emerging tools, frameworks, and techniques for adoption.