AI Forward Deployed Engineer

ECI•New York, NY

22h•$140,000 - $170,000•Hybrid

About The Position

ECI is seeking an AI Forward Deployed Engineer to help investment firms—including hedge funds, private equity firms, investment banks, and family offices—apply AI to their businesses. This hands-on, client-facing engineering role identifies high-value opportunities across deal flow, research, trading, portfolio management, risk, valuations, and middle- and back-office operations, then builds, deploys, and drives adoption of production solutions. The role operates at the FDE level and requires 2 to 5 years of professional software engineering experience. The engineer runs defined workstreams within client engagements and works directly with client teams, while a Senior FDE is accountable for the overall client relationship and engagement. The position is hybrid in New York, with regular work at client sites in the New York area and occasional travel. ECI serves alternative investment and banking firms across the United States, United Kingdom, APAC, and India, providing infrastructure, security, operations, and AI solutions within client environments. Through the ELLA platform and technology partnerships, ECI builds and operates practical AI solutions designed for measurable outcomes, secure data handling, and continuous improvement.

Requirements

Two to five years of professional software engineering experience, including experience supporting production systems.
Hands-on experience building and shipping LLM-powered features, agents, or AI-enabled workflows to production users.
Strong programming skills in TypeScript or Python, including development of APIs, integrations, and data workflows.
Experience with retrieval, evaluation, and guardrails for LLM applications, including work across more than one model provider.
Experience integrating third-party systems and APIs and handling authentication, permissions, data access, and failure conditions.
Experience using AI coding agents, with the judgment to review, correct, test, and verify generated output.
Ability to understand business processes quickly, communicate technical choices clearly to non-technical stakeholders, and work directly with clients with a high degree of autonomy.
Ability to work independently with moderate supervision while coordinating closely with a Senior FDE and distributed ECI teams.
Ability to work regularly at client sites in the New York area and travel occasionally for business.
Ability to manage multiple client priorities and respond flexibly to deadlines, production issues, and changing engagement needs.
Ability to work beyond normal business hours when necessary to support client delivery, releases, or critical business cycles.
Ability to operate a computer keyboard, mouse, and other standard office technology for extended periods.
Client onboarding may require background checks, security attestations, personal-trading pre-clearance, holdings reporting, or other controls required by the client.

Nice To Haves

Experience in a client-facing engineering role and exposure to hedge funds, private equity, investment banking, asset management, fund administration, or other regulated financial-services environments.
Experience with Azure, Azure AI Foundry, infrastructure as code such as Terraform, and Microsoft 365 technologies including Entra ID, Microsoft Graph, Teams, and SharePoint.
Familiarity with investment-industry systems, data, and workflows, including portfolio or order management, fund accounting, research management, market data, private-markets platforms, compliance archiving, reconciliation, or investor reporting.

Responsibilities

Run defined workstreams within AI client engagements, working directly with client business and technical teams and coordinating with the Senior FDE responsible for the engagement.
Map client workflows and identify opportunities for AI to save time, reduce risk, or improve quality across investment research, deal flow, trading, portfolio management, risk, valuations, fund operations, investor relations, and compliance.
Translate business needs into prioritized, buildable use cases with clear success measures based on value, data access, risk, and implementation effort.
Build and deploy AI agents, integrations, and workflows using TypeScript or Python, ECI platforms, AI coding tools, Azure AI Foundry, Microsoft 365, and appropriate specialist products.
Integrate solutions with client systems, APIs, documents, and data, addressing authentication, permissions, data isolation, audit trails, records retention, retries, and partial failures.
Design evaluations using client examples, verify AI-assisted code and outputs, and apply automated checks and human review before production.
Partner with client compliance, security, and IT teams to establish data-handling requirements, approvals, information barriers, and production controls.
Train users, measure adoption and results against agreed success measures, iterate based on feedback, and document operating procedures and runbooks for handover.
Convert recurring client needs into reusable patterns, connectors, and agent skills, and share field insights with ECI product and engineering teams.