TIFIN

AI for Wealth

Staff AI Engineer

AI EngineerMachine Learning EngineerFull TimeRemoteTeam 201-500Since 2018H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

12 days ago

Salary

$190K - $225K / year

PythonLLMGenerative AIMulti Agent SystemsPydantic AIAgent HarnessTool CallingCode ExecutionKnowledge GraphsLLM Fine TuningReinforcement LearningDistributed SystemsAWSDockerMonitoringEvaluation FrameworksVector DatabasesOrchestrationCompliance

Job Description

WHO WE ARE

TIFIN builds AI-powered financial technology that personalizes and improves financial advice across consumers, advisors, workplaces, and institutions. Our modular platform embeds finance-tuned AI to deliver dynamic, tailored guidance at scale—without added complexity. Combining proprietary models, specialized data, and a fast-paced engineering culture, we create secure, compliant tools that power real outcomes. Other differentiators include:

  • Speed: Our ability to stand up businesses at 2-4x the speed of typical fintech companies (building MVPs in 3 months and production-ready products in 6-12 months)
  • Track Record: Previous exits include 55ip (acquired by J.P. Morgan) and Paralel
  • Strategic Partners: Partners include J.P. Morgan, Franklin Templeton, Morningstar, Broadridge, Hamilton Lane, Motive Partners and SEI. 
  • World-Class Team: Complimentary financial services & technical expertise from Google, Microsoft, Uber, PayPal, eBay, Techstars, BlackRock, LPL, Franklin Templeton, Morgan Stanley, Broadridge and more. 

OUR VALUES: Go with your GUT

  • 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

As we scale our AI platform, we are building production-grade multi-agent systems that power advisor copilots, investment intelligence workflows, and autonomous research capabilities. We are seeking a Staff AI Engineer to architect, build, and operationalize these systems at scale. This is a hands-on, high-impact engineering role focused on shipping reliable, enterprise-ready agentic AI systems into production.

PROJECTS

  • Advisor Copilot (Multi-Agent Systems)
    Build a production-grade, multi-agent copilot for financial advisors that retrieves and reasons over client data, analyzes portfolio exposures and risk scenarios, generates personalized insights, enforces compliance guardrails, and drafts client-ready communications — all within a monitored, auditable architecture.
  • Workflow Automation
    Design end-to-end AI workflows spanning client discovery, investment research synthesis, portfolio construction and optimization, and compliant meeting preparation — replacing fragmented tools with intelligent, autonomous systems.
  • AI Agent Platform & Infrastructure
    Architect a scalable multi-agent platform with orchestration engines, memory and state management, dynamic tool invocation, 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 using modern agent frameworks (e.g., Pydantic AI, Agent Harness, Tool-Calling, Code Execution)
  • Build agent workflows that integrate context retrieval, reasoning, tool execution, validation, and compliance checks, 
  • Develop distributed services for agent execution with strong observability, monitoring, and failure handling
  • Establish evaluation frameworks for multi-step reasoning accuracy, groundedness, hallucination mitigation, and financial correctness
  • Implement memory management, context handling, and agent state persistence strategies
  • Partner with product, design, and engineering teams to translate business requirements into robust agent architectures
  • Optimize systems for latency, cost efficiency, and reliability in production
  • Contribute to infrastructure decisions around model serving, vector databases, caching, and orchestration layers

WHAT YOU’LL BRING

  • 3+ years of experience building and shipping Generative AI and LLM applications into production, 6+ years of ML experience.
  • Demonstrated experience designing and deploying multi-agent systems of various architecture
  • Strong experience with multimodal LLMs, knowledge graph, data synthesis, LLM fine tuning, reinforcement learning, agent harness, agent memory
  • Deep proficiency in Python and modern AI frameworks
  • Experience with distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerized deployments
  • Experience implementing monitoring, evaluation, and reliability safeguards for AI systems
  • Strong systems thinking — ability to design beyond single-model solutions toward coordinated, multi-component architectures
  • Resilience and adaptability - experience working at early-stage startups is a plus

COMPENSATION RANGE

$190,000 - $225,000 USD

In addition to cash compensation, a meaningful equity stake is a significant part of the overall package. Package also includes benefits program eligibility: Comprehensive health, dental and vision coverage, retirement benefits and flexible PTO. 

TIFIN is proud to be an equal opportunity workplace and values the multitude of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status.

Please see more details on our privacy practices in our Privacy Notice here.

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