About the Role
OUTCOME ENGINEERS needed at one of our Agentic AI Investment Technology STARTUPS!!! Hybrid 3x per week in office in NYC only. Base $175k - $200k plus bonus and EQUITY. Must have 4+ years of experience in financial analysis, investment research, credit underwriting, portfolio monitoring, or equivalent analytical roles. Background in investment banking, private credit, private equity, asset management or consulting is ideal as well as proficiency in Python and/or SQL. Must have some experience with AI/LLMs as well.
Our client develops autonomous AI agents that eliminate the repetitive, manual work slowing down financial institutions. Their technology supports credit, investment, ESG, and compliance workflows for leading asset managers, PE firms and investment banks.
What You’ll Do:
You will own a portfolio of financial clients and become their go-to technical partner. You will work closely with Credit, Investment, Research, and Portfolio Monitoring teams to:
Understand and map financial workflows end-to-end. Some examples are:
“Automate quarterly credit reviews using borrower KPIs + news + filings”
“Build investment screens that collapse hours of research into minutes”
“Automate portfolio monitoring reports used by ICs”
Sit deeply inside customer workflows, joining working sessions, shadowing analysts, and understanding decision-making so you can define KPIs, and ROI for workflow automation.
Translate ambiguous analyst processes into clear, structured, multi-step agent workflows. You build the functioning prototypes for Product Engineers to scale.
Own the correctness of the workflow: design the evaluation criteria, edge-case handling, error paths, and audit logic that engineers implement at scale
Plan and manage multi-threaded client projects end-to-end across Business, Security, and Procurement with clear ownership of timelines, risks, and stakeholder communication
Own the success of pilots through to production and expansion, working with sales to turn value delivered into renewed contracts and upsells
Proactively surface and shape new use cases, teams, and regions where the agents can be deployed, and help build the commercial case for expansion.
Build adoption: create super-user networks, internal champions, and usage cadences so workflows become part of daily decision-making.
Partner with Product Engineers to convert every deployed workflow into reusable templates, patterns, and components.
Spot cross-client patterns and feed them into the product roadmap.
Shape financial workflows product strategy - identify which use cases matter most, which markets have the highest pull, and what features unlock scale.
Represent the firm as a subject-matter expert with clients, analysts, and industry teams.
Provide feedback to engineering on primitives, orchestration, evals, model behavior, and platform improvements.
Help build case studies, playbooks, and proof points that consistently win deals.
Mentor junior team members, and over time help build and lead a high-performance Financial Workflows OE pod.
Long-Term Ownership
Over time, grow into an owner of a functional vertical (Credit, Monitoring, Investment Research, etc.), with input into revenue targets, pricing, customer segments, roadmap, and commercial priorities.
What We’re Looking For:
Must Haves
4–7+ years experience in financial analysis, investment research, credit underwriting, portfolio monitoring, or equivalent analytical roles.
Working understanding of typical workflows such as:
- Credit memos & annual reviews
- Investment screens & IC memos
- Financial Modeling logic
- Portfolio monitoring and KPI tracking
- Market/industry analysis
- Compliance/ops workflows (non-ESG-specific)
Ability to reverse-engineer financial workflows. E.g You can take a messy 80-page credit memo or IC deck and extract the logic into steps, decisions, and data needs.
Technical literacy. You have Python/SQL proficiency or advanced experience with low-code automation tools. You must be able to vibe code a demo to unblock yourself.
You’ve built or designed a multi-step LLM workflow before.
You ship V1s in days, not weeks, and iterate directly with clients
Strong workflow-design and prompt-engineering intuition and experience designing structured, multi-step AI workflows.
Experience working directly with institutional clients (PE/credit/AM, IB, consulting, data vendors).
Ability to run discovery, define scope, manage stakeholders, and present outputs clearly.
Track record of delivering complex, multi-stakeholder projects with speed and autonomy.
Evidence of commercial impact: renewals, upsells, new use cases, or adoption wins.
Nice to Haves
Background in IB, private credit, PE, asset management, or consulting.
Experience with OpenAI/Claude, LangChain, workflow automation tools, or custom LLM systems.
Familiarity with deal structures, capital stacks, covenants, risk frameworks, or sector dynamics.
Experience influencing or owning a product line or book of business.
Understanding of financial data providers/ecosystem (Bloomberg, FactSet, PitchBook, Preqin, Refinitiv).
Understanding of enterprise data/security environments
Soft Skills We Value
Customer empathy: You think like an analyst, what inputs they trust, how they validate, how they make decisions
Structured translator: You turn unstructured analyst thought processes into clear steps, logic, and evaluation criteria for engineers to implement
Comfortable in ambiguity: You can make progress with imperfect information, navigate complex organizations, and bring structure where there isn’t any
Proactive problem-solver: You anticipate issues before the client does
Hustle & ownership: You take responsibility end-to-end and care deeply about outcomes
Curious & fast learner: You quickly understand new workflows, industries, and agent capabilities. You can quickly test, evaluate, and integrate new AI capabilities into client workflows.
Executive presence: You can credibly advise senior stakeholders and guide decisions. You can talk to customers in business language and translate into structured technical requirements.
Commercial instinct: You naturally see where a workflow can extend to new teams or processes and can help shape that into a concrete opportunity.