Vanilla
The Software Engineer - AI Applications at Vanilla is responsible for developing AI-powered applications using existing Large Language Models (LLMs) to enhance estate planning processes. This role involves building microservices, managing data ingestion, and collaborating closely with product and engineering teams to create efficient model training and deployment pipelines. Candidates should have strong proficiency in modern programming languages like Python or JavaScript and experience with integrating AI technologies to deliver high accuracy solutions.
Headquarters
Bellevue, Washington, United States
Company Size
51-200 employees
Founded
2019
Vanilla is a leading estate advisory platform that offers innovative and AI-powered software to help financial advisors streamline the estate planning process. It enables users to create personalized estate plans, visualize complex strategies, and enhance client engagement through dynamic visualizations and document automation. Vanilla’s solutions are tailored for wealth management professionals and designed to simplify estate planning for clients, thereby increasing advisor efficiency and strengthening client relationships. With a focus on collaboration, compliance, and customer support, Vanilla is transforming how estate planning is approached in the financial advisory space.
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Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Vanilla.
Vanilla didn’t post a salary, so this is our estimate from similar listings.
Wealth.com and Vanilla are extending their reach among advisors
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Staff Software Engineer - AI Applications
Vanilla
LLM Full Stack Engineer
Accenture
Senior AI Scientist
Cornerstone Research
Lead the team in: research, design, development, and deployment of advanced AI agents and agentic systems. Architect and implement complex multi-agent systems, including planning, decision-making, and execution capabilities. Develop and integrate large language models (LLMs) and other state-of-the-art AI techniques to enhance agent autonomy and intelligence. Build robust, scalable, and reliable infrastructure to support the deployment and operation of AI agents at scale. Diagnose and troubleshoot issues in complex distributed environments and optimize system performance. Contribute to the team's technical growth and knowledge sharing. Stay up-to-date with the latest advancements in AI research and agentic AI and apply them to our products. Leverage enterprise data, market data, and user interactions to build intelligent and personalized agent experiences. Knowledge and passion in machine learning algorithms, Gen AI, LLMs, and natural language processing (NLP). Understanding of agent-based modeling, reinforcement learning, and autonomous systems. Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning. Experience with large language models (LLMs) and their applications in Agentic AI. Proficiency in programming languages such as Python, and experience with machine learning frameworks like TensorFlow or PyTorch. Experience with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes). Understanding of distributed system design patterns and microservices architecture. Excellent problem-solving and data analysis skills. Strong communication and collaboration skills. Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience. Min 6-10-+ years of relevant work experience in AI, Machine Learning, and applying data science to real-world use cases. Strong track record of taking systems from prototype to production with a focus on scalability and reliability. Knowledge of fine-tuning strategies (QLORA, DPO) and inference optimization (vLLM, TensorRT-LLM). Research experience in agentic AI or related fields. Experience building and deploying AI agents in real-world applications. Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions.
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