AI Engineering

WHO WE ARE

TIFIN builds the AI operating layer for wealth. Our platform delivers agentic workflows across the industry’s core personas—investors, advisors, investment teams, and operations—so financial institutions can move faster, serve more clients, and deliver better outcomes with the same (or fewer) resources. We combine finance-native AI, specialized data, and enterprise-grade controls to deploy secure, compliant capabilities into real production environments.

WHAT SETS US APART Speed: We build and ship quickly—MVPs in ~3 months, production-ready products in ~6–12 months. P. P.

Morgan, SEI, Franklin Templeton, Morningstar, FactSet, Broadridge, Motive Partners and Tectonic Ventures. World-Class Team: Complimentary expertise across AI and financial services, with experience from Google, Microsoft, Uber, PayPal, eBay, BlackRock, LPL, Franklin Templeton, Morgan Stanley, Broadridge and more. OUR VALUES Grow at the Edge.

We are driven by personal growth fueled by a beginner’s mindset. We get out of our comfort zone and keep egos aside. With self-awareness and integrity we strive to be the best we can possibly be.

No excuses. Understanding through Listening and Speaking the Truth. We communicate with authenticity, precision and integrity to create a shared understanding.

We identify opportunities within constraints and propose solutions in service to the team. I Win for Teamwin. We believe in staying within our genius zones to succeed and taking accountability for driving results.

We are all individual contributors first and always thinking about what can be better. ROLE OVERVIEW Our north star is delivering better wealth outcomes for more people. We’re building production-grade multi-agent systems that power advisor copilots, investment intelligence workflows, and autonomous research capabilities.

Our AI Engineers architect, build, and operationalize these systems at scale, pushing the boundaries of what agentic AI can do. We’re hands-on engineers focused on shipping reliable, enterprise-ready agentic AI systems into production. PROJECTS Agent Advisor Copilot.

Build a production-grade, multi-agent copilot for financial advisors that retrieves and reasons over client data using RAG and a persistent knowledge graph of clients and holdings, analyzes portfolio exposures and risk scenarios, generates personalized insights, enforces compliance guardrails, and drafts client-ready communications — all within a monitored, auditable architecture graded by automated evals and LLM-as-judge review. Deep Research Workflow Agents. Design end-to-end AI workflows spanning client discovery, investment research synthesis, portfolio construction and optimization, and compliant meeting preparation — powered by deep research agents that reason over live web and internal data in ReAct-style loops — replacing fragmented tools with intelligent, autonomous systems.

Agentic Infrastructure Reasoning Stack. Architect a scalable multi-agent platform on LangGraph-style orchestration, with agent memory and state management, dynamic tool invocation, model fine-tuning pipelines, structured output validation, observability, fault tolerance, and automated evaluation — solving reliability, explainability, and regulatory challenges at scale.

WHAT YOU’LL DO

Design and implement production-grade multi-agent systems and ReAct-style reasoning loops using modern agent frameworks and orchestration engines (e.g., LangGraph, Pydantic AI, Agent Harness, Tool-Calling, Code Execution) Build agent workflows that integrate RAG-based retrieval, agent memory, and knowledge graphs for grounded, long-horizon reasoning, fine-tuning models where prompting and retrieval alone fall short Establish evaluation and benchmarking frameworks, including LLM-as-judge pipelines, for multi-step reasoning accuracy, groundedness, hallucination mitigation, and financial corr