Forward Deployed AI Engineer

This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone.

Our client operates a large verified healthcare professional community spanning approximately 150 countries and provides real-time research and data products for pharmaceutical, biotech, and medical device clients.

Role Overview

The Forward Deployed AI Engineer, Delivery and Operations will embed directly with Delivery and Operations teams to redesign the survey lifecycle around AI agents, from translating client requirements into completed surveys to fielding surveys to the appropriate healthcare professionals and engaging external vendors when additional responses are required.

This is a hands-on engineering role responsible for understanding existing workflows and then designing, building, testing, deploying, and improving agent-first solutions alongside Delivery, Operations, and Engineering.

Location

Fully Remote | 9:00 AM - 5:00 PM EST | LATAM

Key Responsibilities

Workflow Discovery & Agent-First Design

• Embed with Delivery and Operations to map the survey lifecycle from end to end, including tools, handoffs, exceptions, approvals, and bottlenecks.

• Establish measurable baselines for existing workflows before implementing automation.

• Redesign workflows around AI agents rather than adding AI to existing processes.

• Identify and prioritize additional AI opportunities across Delivery.

AI Agent & Workflow Development

• Design and build AI-powered workflows using document extraction, structured outputs, workflow routing, and agentic task execution.

• Develop integrations through APIs, webhooks, and automation tools.

• Build evaluations and monitoring for AI-powered workflows and non-deterministic systems.

• Design production workflows with human-in-the-loop controls, including approval checkpoints, review queues, guardrails, audit trails, and exception handling.

• Document systems, workflow logic, prompts, and operating procedures.

Vendor Engagement Automation

• Build an AI agent that identifies when external vendor support is required based on internal feasibility or response volume.

• Automate approved vendor outreach and follow-up workflows.

• Organize vendor responses and support negotiation within agreed rate cards.

• Support survey-link testing as part of the vendor engagement process.

• Incorporate historical bid and pricing data into the workflow.

• Escalate decisions requiring human approval.

• Improve the speed of vendor engagement and quote turnaround.

Survey Creation & Translation

• Build workflows that extract and structure survey requirements from source documents.

• Draft surveys within internal tooling based on extracted requirements.

• Identify unclear requirements and route them to appropriate reviewers.

• Improve AI-assisted translation workflows.

• Support selective re-translation of modified survey questions.

• Implement quality checks and human review steps.

• Build on or replace existing internal tools while maintaining required data-handling and security standards.

Fielding & Audience Targeting

• Improve workflows for reaching healthcare professionals based on specialty, country, screening criteria, exclusions, and participation history.

• Monitor survey responses and identify surveys at risk of missing required volume or timelines.

• Recommend appropriate next actions based on fielding performance.

• Support fielding activity managed through Salesforce.

• Improve how incentives are set to drive timely responses.

• Work alongside the existing AI screener-matching tool rather than rebuilding it.

Systems Integration & Collaboration

• Connect AI workflows with homegrown survey platforms and Salesforce.

• Work with internal engineers on deeper platform changes when required.

• Collaborate directly with Delivery, Operations, and Engineering teams.

• Translate complex workflows from non-technical operators into practical tools they can use.

• Influence stakeholders across teams without direct management authority.

Measurement & Optimization

• Track workflow adoption, response rates, turnaround time, and time saved against established baselines.

• Monitor production workflows and refine them with workflow owners.

• Use measurable results to guide improvements and prioritize future AI initiatives.

Qualifications

Experience

• 5+ years of software engineering experience , including 2+ years building and deploying AI-powered workflows, agents, or automation in production business environments .

• Experience completing an agent-first redesign of a real business workflow, including establishing a baseline, redesigning the process, defining human responsibilities, and measuring results.

• Hands-on LLM experience with document extraction, classification, structured outputs, workflow routing, and agentic task execution.

• Experience evaluating non-deterministic systems.

• Production engineering experience with Python and at least one typed programming language.

• Experience integrating CRMs, internal tools, APIs, and data systems.

• Experience building human approvals, review queues, exception handling, and quality controls into production systems.

• Proven experience working directly with non-technical operators and translating complex workflows into practical tools.

• Ability to work from directional guidance and influence stakeholders without direct management authority.

• BS in Computer Science or a related field, or equivalent practical experience.

• Ability to travel occasionally to the US.

• US VISA as a tourist.

• Must be fluent in English & Spanish

Skills

• Strong Python development skills and experience with at least one typed language.

• Strong understanding of LLM-powered workflows, AI agents, and production automation.

• Ability to work with document extraction, classification, structured outputs, workflow routing, and agentic task execution.

• Ability to evaluate and monitor non-deterministic AI systems.

• Strong integration skills across APIs, webhooks, CRMs, internal tools, and data systems.

• Ability to design human-in-the-loop controls, approval checkpoints, review queues, guardrails, audit trails, and exception handling.

• Ability to establish measurable workflow baselines and evaluate automation impact.

• Ability to document systems, workflow logic, prompts, and operating procedures.

Preferred Experience

• Salesforce, including workflows, data structures, outreach, and activity tracking.

• C#/.NET, React, and TypeScript environments.

• Connecting AI workflows with homegrown platforms.

• Healthcare, market research, survey operations, or other regulated and data-sensitive environments.

• Multilingual or translation workflows.

• Zapier or similar automation platforms.

• LLM observability, prompt and version management, and reliability testing.

Technical Environment

• C#/.NET

• React

• TypeScript

• AWS

• Salesforce

• Zapier

• Amazon Bedrock

• AgentCore

• Claude models

• MCP

• Redshift

• Databricks

What Success Looks Like

First 30 Days

• Spend time with Delivery teams in the U.S. and Mexico.

• Build relationships across Delivery, Operations, and Engineering.

• Map vendor engagement, survey creation, and fielding workflows, including baselines, decision points, and required approvals.

• Establish a phased implementation plan with vendor engagement as the first pilot.

Opportunity

The Forward Deployed AI Engineer, Delivery and Operations will have the opportunity to redesign operational workflows around production AI agents rather than simply adding AI capabilities to existing processes.

The role provides hands-on ownership across discovery, workflow design, engineering, integrations, controls, deployment, evaluation, and optimization, with opportunities to expand AI automation across Delivery operations.

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