AI Platform Engineer

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October 29

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SigFig

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Finance • Fintech • SaaS

SigFig is a digital wealth management company providing comprehensive digital solutions for financial institutions, wealth management firms, insurance companies, and individual investors. It offers a suite of interconnected digital wealth solutions designed to empower financial advisors and clients with personalized investment options tailored to unique financial goals. SigFig aims to streamline client onboarding, account opening, and product suitability, enhancing the efficiency of financial services across various segments. Its platform helps advisors attract new client segments, manage portfolios, and deliver client-centric services efficiently. The company's technological innovations in digital finance provide a seamless investment experience and contribute to financial wellness.

201 - 500 employees

Founded 2012

💸 Finance

💳 Fintech

☁️ SaaS

💰 $50M Series E on 2018-06

📋 Description

• Design and build the core AI platform services that power advisor-facing features such as intelligent insights, meeting summaries, and next-step recommendations. • Develop and maintain retrieval-augmented generation (RAG) and semantic search pipelines that allow our models to access and reason over financial data securely and efficiently. • Integrate foundation models (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or open-source alternatives) into scalable microservices and APIs. • Create and manage prompt orchestration and versioning frameworks to support consistent and reliable AI responses across products. • Develop evaluation, monitoring, and observability systems to ensure AI quality, compliance, and performance in production. • Optimize inference performance, latency, and cost through model routing, caching, and fine-tuning strategies. • Collaborate closely with product teams to enable new AI capabilities and ensure that AI outputs align with financial domain standards and regulations. • Stay current with LLM and agentic technology advancements and help shape how Tandems applies them to real-world advisor workflows.

🎯 Requirements

• 4+ years of software engineering experience with production systems • Strong proficiency in Python and hands-on experience with LLM application frameworks (LangChain, LlamaIndex, Semantic Kernel, or DSPy) • Proven experience building agent workflows and orchestrating multi-step AI processes • Deep understanding of foundation model APIs (OpenAI, Anthropic, Google AI, AWS Bedrock, Azure OpenAI, or open-source models via Replicate/Hugging Face) • Experience with prompt engineering, including techniques like few-shot learning, chain-of-thought, and prompt chaining • Hands-on experience implementing RAG (Retrieval-Augmented Generation) systems with vector databases • Building autonomous and semi-autonomous agent systems that can plan, use tools, and execute multi-step tasks • Implementing tool-calling and function-calling patterns with LLMs • Creating agent memory systems (conversation history, long-term memory, knowledge bases) • Orchestrating multi-agent systems or agent handoffs • Experience with agent evaluation, debugging, and observability (using tools like LangSmith, Weights & Biases, or custom solutions) • Managing different foundation models for specific tasks (routing between models based on complexity/cost/speed) • Implementing streaming responses and real-time user interactions • Handling context window management and conversation pruning strategies • Building fallback and error recovery mechanisms for AI systems • Cost optimization and rate limit management across multiple model providers

🏖️ Benefits

• Tax-friendly Compensation • Liberal Leave Policy • Medical cover for the family, including parents • Quarterly Wellness Benefit • WFH Allowance • Mobile/Internet subsidy (for smooth WFH experience) • Employee Referral Program • Employee Recognition Program • And more!