Senior AI Engineer

Affinity stitches together billions of data points from massive datasets to create a powerful, accurate representation of the world's professional relationship graph. Based on this data, we offer our users the insights and visibility they need to nurture and tap into the opportunities in their team's network. 

This role is part of the AI Platform team, which owns the AI services that power Affinity's industry-leading relationship intelligence platform. We extract and retrieve information from billions of structured and unstructured data points to deliver actionable insights to customers.

As a Senior AI Engineer, you will collaborate with machine learning engineers, data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. You will design and build LLM-powered AI systems that efficiently uncover insights from compelling business interaction data – an exciting and unique opportunity within the industry. 

In this role, you will:

• Build RAG systems: Architect, prototype, and deploy RAG pipelines, combining vector search, hybrid retrieval, reranking and contextual compression techniques. 
• Build LLM powered agent systems: Contribute to design and orchestration of multi-agent LLM systems using community frameworks and custom orchestration layers. 
• Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data. 
• Collaborate cross-functionally: Partner with cross-functional (product, infra, data engineering, and software engineering) to build robust, high-scale systems that underlie all of our data processing and ML Operations.

Qualifications

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Required:

• 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production. 
• Hands on experience with LLM applications in production including prompt engineering and utilizing frameworks for online and offline evaluation
• Experience with LLM assisted search, such as query understanding and augmentation, text2sql, and entity extraction   
• Experience with vector or graph databases
• Experience with document chunking, embedding models, and context window optimization
• Familiarity with metadata-based retrieval and re-ranking strategies
• Hands on experiences with model evaluation metrics (e.g. perplexity, hallucination rate, factual consistency)   
• Familiarity with data security, versioning, and MLOps principles

Nice to Have:

• Experience with enterprise AI applications with strict compliance, audit, or legal requirements
• Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvements. 
• Experience with multi-modal search
• Experience with graph based recommendation systems, such as graph NN. 
• Experience with developing AI applications powered by agent-based systems
• Experience with packaging, CI/CD and pipeline automation. 

Tech stack: Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference. 

How we work:

Our culture is a key part of how we operate, as well as our hiring process:

• We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
• We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with. 
• We make data-driven decisions and make the best decision for the moment based on the information available.

If you’d want to learn more about our values click here.

Work Location: San Francisco, New York, or US Remote (Affinity is registered to employ in certain U.S. states)

For those located in San Francisco or New York, for this role we're embracing a hub-hybrid model, designed to balance flexibility with meaningful in-person collaboration. Team members within commuting distance are expected in-office 2–3 days per week, typically Tuesday through Thursday. We believe great things happen when people come together intentionally to connect, create, and build momentum as a team.

What you'll enjoy at Affinity:

• We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.
• Health Benefits: We cover your medical, dental, and vision insurance premiums with comprehensive PPO, HDHP and HMO options (in CA), and offer flexible personal & sick days to support your well-being.
• Retirement Planning: We offer a 401(k) plan to help you plan for your future.
• Learning & Development: We provide an annual education budget and a comprehensive L&D program.
• Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
• Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.

Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job.

A reasonable estimate of the current range is $160,000 to $235,000 USD. Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant.