Forward Deployed Insights Engineer (Applied AI)

Translucent

$180K — $230K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of deep healthcare domain experience in consulting, health tech, or finance data
  • Proficient in Python and SQL for scripting and data manipulation
  • Hands-on experience with AI-assisted coding tools in workflow
  • Familiar with AI/ML projects and agentic systems
  • Comfortable building visualizations (dashboards, BI tools) for data presentation
  • Experience presenting technical solutions to non-technical stakeholders
  • Strong ability with version control and CI/CD workflows

Responsibilities

  • Configure workspaces and develop AI agents and ML models for customer needs
  • Collaborate closely with customers to identify high-value healthcare finance problems
  • Design visualizations for data outputs, enabling actionable insights for leaders
  • Present ML/AI solutions directly to end users to enhance business trust
  • Collaborate with product teams to transform customer solutions into platform-wide features
  • Validate models and agents for reliability and trustworthiness in outputs

Benefits

  • High-ownership position with a significant impact on customer solutions
  • Opportunity to work directly with clients in the healthcare finance sector
  • Engagement with cutting-edge AI and ML system development
  • Flexible and innovative work environment
  • Collaborative team dynamic that focuses on problem-solving
  • Location in vibrant Union Square, NYC, fostering a strong team culture
Full Job Description
About the role

We're hiring a Forward Deployed Insights Engineer to join our team in New York. You will sit at the intersection of our customers' healthcare finance problems and the agentic AI and ML systems we build to solve them. Working on top of the unified data ontology our Analytics Engineers maintain and the agent infrastructure our AI Engineering team builds, you will stand up new agents and ML models for specific customer problems, configure the visualizations and presentation layer that make their outputs usable, and work directly with customers and end users to turn those capabilities into real, trusted decisions.

This is a high-ownership, customer-facing role. You will partner closely with our product team to make sure the solutions you build for one customer become repeatable, platform-wide offerings.
What you'll do
  • Configure customer workspaces and build new AI agents and ML models on top of existing agent infrastructure and platform capabilities - our AI Engineering team owns agent infra, development harnesses, and core architecture, so you're focused on building for the customer problem, not the underlying framework.
  • Work directly with customers and our product team to scope solutions that solve real, high-value problems in healthcare finance.
  • Configure the visualizations and presentation layer for the data, trends, and insights your agents and models generate - turning model output into something a finance or operations leader can act on.
  • Present and demo ML/AI solutions directly to end users - translating technical capability into business trust.
  • Partner with product to generalize customer-specific solutions into reusable, platform-wide features.
  • Validate the correctness and reliability of the agents and models you ship, and build the testing rigor needed to earn customer trust in AI-generated outputs.
What we're looking for
Must-haves
  • Deep healthcare domain experience - consulting, forward-deployed, or health tech background, with hands-on exposure to claims, EHR, or financial/revenue cycle data.
  • Strong Python and SQL.
  • Real, hands-on experience using AI-assisted coding tools (e.g., Cursor, Claude Code) in your day-to-day workflow.
  • Exposure to AI/ML projects or programs - agentic systems, applied ML, or similar.
  • Comfort building visualizations or front-end presentation layers for data and analytical output (e.g., dashboards, BI tools, or lightweight front-end frameworks).
  • Experience working directly with end users, including presenting technical or AI/ML solutions to non-technical stakeholders.
  • Strong experience with version control and gitops workflows - you're comfortable owning changes through code review and shipping them via automated CI/CD, not just committing code.
Nice-to-haves
  • GCP experience.
  • Experience productizing a bespoke customer solution into a reusable, platform-wide feature.
Education

Bachelor's degree (or higher) in computer science, data science, statistics, mathematics, or a related quantitative field - or equivalent experience building and deploying applied ML/AI solutions. Advanced degrees (MS in a quantitative field) are a plus but not required; we weigh hands-on AI/ML build experience and healthcare domain exposure over formal credentials.
Location

Union Square, New York City. In-office 4 days per week.
Compensation

$180k - $230k

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