Forward Deployed Engineer

Infused Solutions; New York (NY); On-site; USD 160,000 - 200,000; Full time

Job summary

Infused Solutions' client is a fast-growing AI platform serving institutional finance clients. They automate complex analyst workflows—turning days of manual work into minutes—for some of the world's largest financial institutions.

You will shadow analysts, design multi-step AI agent logic, and prototype V1s in days, presenting to partners. You are an IC, hands-on, bridging business problems to technical solutions and delivering value quickly.

Qualifications

• Institutional finance analyst background (4-7+ years) in IB, PE/credit, or asset management.
• Self-taught coder with Python/SQL; able to prototype workflows.
• Built something with LLMs in the last 12 months (RAG pipeline, agentic workflow, document automation).
• Bridge analyst and CTO: translate business problems into technical requirements.
• Ship fast: V1 in days, iterate on feedback.

Responsibilities

• Shadow credit analysts at PE firms and asset managers; reverse-engineer workflows.
• Design multi-step AI agent logic to automate workflows.
• Prototype and ship V1s in days; present to partners/C-suite.
• Manage scope; drive adoption; hand prototypes to engineers for productization.

Skills

Institutional finance analysis

Prototyping

LLM workflows

Stakeholder communication

Tools

Python

SQL

LangChain

Job description

Compensation: $160K-$200K base + 20 - 30% bonus + equity

Job Type: Permanent

Infused Solutions' client is a fast-growing AI platform serving institutional finance clients. They automate complex analyst workflows-turning days of manual work into minutes-for some of the world's largest financial institutions.

30% financial analyst (understand workflows intimately) + 30% product strategist (translate needs into solutions) + 40% hands-on builder (prototype and ship working AI agents)

You will:

• Shadow credit analysts at PE firms and asset managers, reverse-engineer their workflows (IC memos, deal screening, portfolio monitoring, credit risk)
• Design multi-step AI agent logic that automates those workflows
• Prototype and ship V1s in days, present to partners/C-suite
• Manage scope, drive adoption, hand prototypes to engineers for productization

You won't:

• Build production infrastructure (that's Product Engineers)
• Manage a team (you're IC, hands-on)
• Sit in an office writing requirements doc (you're embedded with clients)

Must-Haves

• Institutional finance analyst background (4-7+ years)
  IB (credit, DCM, leveraged finance), PE/credit, or asset management. You know what an IC memo looks like and have built financial models at 2 AM.
• Self-taught coder
  Python, SQL, basic scripting. You can prototype and automate your own workflows (Excel -> Python -> Lang Chain).
• Built something with LLMs in the last 12 months
  RAG pipeline, agentic workflow, document automation-anything. You've shipped something real (internal tool, side project, client prototype).
• Bridge analyst and CTO
  Translate business problems into technical requirements. Explain AI limitations to skeptical partners. Push back on scope creep.
• Ship fast
  V1 in days, not months. You're comfortable with "good enough to prove value" and iterate based on feedback.