
501 - 1000 employees
Founded 2013
💸 Finance
💳 Fintech
☁️ SaaS
💰 $130M Corporate Round on 2021-11
Finance • Fintech • SaaS
Addepar is a comprehensive technology and data platform designed to streamline wealth management for investment professionals globally. It empowers firms with sophisticated tools to manage complex investment portfolios, offering features like data aggregation, portfolio trading, portfolio modeling, and fee tracking. With over $6 trillion in assets managed, Addepar serves a variety of financial services including wealth managers, family offices, private banks, and broker-dealers. It supports more than 45 markets worldwide and provides customizable reporting and integration solutions, facilitating better decision-making and client satisfaction.
🔥 2 minutes ago
🇺🇸 United States – Remote
💵 $163k - $203.5k / year
⏰ Full Time
🟢 Junior
🟡 Mid-level
🛠️ Implementation Specialist
🦅 H1B Visa Sponsor
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501 - 1000 employees
Founded 2013
💸 Finance
💳 Fintech
☁️ SaaS
💰 $130M Corporate Round on 2021-11
Finance • Fintech • SaaS
Addepar is a comprehensive technology and data platform designed to streamline wealth management for investment professionals globally. It empowers firms with sophisticated tools to manage complex investment portfolios, offering features like data aggregation, portfolio trading, portfolio modeling, and fee tracking. With over $6 trillion in assets managed, Addepar serves a variety of financial services including wealth managers, family offices, private banks, and broker-dealers. It supports more than 45 markets worldwide and provides customizable reporting and integration solutions, facilitating better decision-making and client satisfaction.
• Build AI-powered agents and tools end-to-end, from client problem identification and rapid prototyping through rigorous evaluation and production deployment • Design and implement LLM integrations, including prompt engineering, function calling, structured outputs, and retrieval-augmented workflows • Define evaluation criteria and build test harnesses for AI systems with ambiguous and domain-specific correctness • Work directly with clients to understand workflows, validate AI behavior, and iterate toward production quality • Partner with core engineering teams to generalize client-specific work into product features • Contribute to shared AI infrastructure, including agent frameworks, tool integrations, and deployment pipelines • Monitor and maintain production AI systems for reliability, cost, and performance
• 2+ years of professional software engineering experience • Professional experience with Python • Experience working with LLM APIs (Claude, GPT, or similar), including function calling and structured outputs • Comfort with SQL for data exploration and data-grounded AI workflows • Experience with AI-assisted development tools (Claude Code, Codex, or similar) • Experience building something from zero to one • Ability to ship quickly, learn from feedback, and iterate • Ability to take projects from prototype to production and focus on client experience • BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience • Applicants must be legally authorized to work in the United States for any employer without current or future visa sponsorship • Must be authorized to begin work in the U.S. on the first day of employment • May require occasional work outside standard business hours to accommodate client time zones • Nice-to-have: experience building agentic systems • Nice-to-have: experience with additional backend languages, especially Java • Nice-to-have: familiarity with financial data • Nice-to-have: exposure to AWS and container-based deployments • Nice-to-have: experience with evaluation frameworks or methodologies for measuring AI system quality
• Bonus • Equity • Benefits • Reasonable accommodation for individuals with disabilities • Equal opportunity and inclusive workplace • Up to 15% travel to client sites, including occasional overnight and multi-day engagements • Remote work arrangement
Apply Now🔥 3 hours ago
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