Forward Deployed AI Engineer, Delivery and Operations

About Sermo

Sermo runs the world's largest verified healthcare professional community, over 1.5 million triple-verified physicians, APPs, pharmacists and other clinicians across roughly 150 countries, and turns that community into real-time research and data products for pharmaceutical, biotech and medical device clients.

The role

You'll embed with Sermo's Delivery and Operations team and redesign the survey lifecycle around AI agents: from turning client requirements into a finished survey, to fielding it to the right healthcare professionals, to bringing in external vendors when more responses are needed. This is hands-on. You'll learn how the work runs today, then design, build, test, deploy and improve agent-first workflows with Delivery, Operations and Engineering. The goal isn't AI bolted onto today's process, but a redesigned workflow where agents do the work and people verify it.

Initial workstreams

Vendor engagement, the first major agent. When internal feasibility or response volume falls short, the team sources additional respondents from external market-research vendors through manual outreach, negotiation and tracking. You'll build the agent that detects when vendor support is needed, sends approved outreach, manages follow-ups, organizes responses, supports negotiation within the agreed rate card, tests survey links, learns from historical bid and pricing data, and escalates decisions that need human approval. Speed to answer is part of the value, since a faster quote wins more of the work.

Survey creation and translation. Client requirements arrive in many formats. You'll build a workflow that extracts and structures requirements from source documents, drafts the survey in internal tooling, flags unclear requirements and routes work to reviewers. You'll also improve AI-assisted translation, including selective re-translation of changed questions, with quality checks and review steps. You'll build on, or replace, the internal tools teams already use, bringing them within Sermo's data-handling and security standards.

Fielding and audience targeting. You'll improve how surveys reach the right healthcare professionals by specialty, country, screening criteria, exclusions and participation history; monitor responses; flag surveys at risk of missing volume or timelines; and recommend next actions, with fielding activity managed through Salesforce. You'll also improve how incentives are set to drive timely responses, and work alongside the existing AI screener-matching tool rather than rebuild it.

What you'll do

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

• Redesign each workflow agent-first and build it: document extraction, structured outputs, routing, agentic task execution, and integrations through APIs, webhooks and automation tools.

• Connect workflows to Sermo's homegrown survey platforms and Salesforce, working with internal engineers on deeper platform changes.

• Design human-in-the-loop controls for every production workflow: approval checkpoints, review queues, guardrails, audit trails and exception handling.

• Build evaluations and monitoring, and track adoption, response rates, turnaround and time saved against the baseline.

• Document systems, workflow logic, prompts and operating procedures so the team can run and improve them.

• Identify and prioritize the next AI opportunities across Delivery.

What you'll bring

Required:

• 5+ years of software engineering, including 2+ years building and deploying AI-powered workflows, agents or automation in production business environments, not only prototypes.

• A completed agent-first redesign of a real business workflow that you can walk through: the baseline, the redesign, what people still do, and the measured result.

• Hands-on LLM experience with document extraction, classification, structured outputs, workflow routing and agentic task execution, plus evaluation of non-deterministic systems.

• Production engineering in Python and at least one typed language, with experience integrating CRMs, internal tools, APIs and data systems.

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

• A proven ability to work directly with non-technical operators and turn complex workflows into tools they use, working from directional guidance and influencing stakeholders you don't manage.

• Strong written and spoken English, and professional Spanish fluency, since you'll work closely with Delivery stakeholders in Mexico.

• Full-time availability in Latin American time zones, collaborating with teams across North America and Europe, with occasional travel to the delivery office in Mexico.

Stretch, for an exceptional candidate:

• Several redesigns led across different functions, and the judgment to decide which workflows are worth doing next and build the business case for them.

• Experience architecting a shared agent platform, evaluation standards or guardrail patterns that other engineers reuse.

• A track record of setting direction across teams and influencing senior leaders.

• Experience mentoring engineers or helping build an applied AI team, and interest in growing into that role here.

Preferred:

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

• C#/.NET, React and TypeScript environments, and connecting AI workflows to homegrown platforms.

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

• Multilingual or translation workflows.

• Zapier or similar automation platforms, and knowing when a purpose-built agent is the better choice.

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

Our stack

Homegrown survey tooling on C#/.NET, React and TypeScript, running on AWS; Salesforce and Zapier; Amazon Bedrock and AgentCore, Claude models and MCP for AI; Redshift and Databricks for data.

Your first 90 days

• 30 days: time on site with the Delivery teams in US and Mexico; relationships built with Delivery, Operations and Engineering; the vendor-engagement, survey-creation and fielding workflows mapped with baselines, decision points and required approvals; a phased plan agreed, with vendor engagement as the first pilot.

• 60 days: the vendor-engagement agent running in shadow mode on real work, with integrations, approval logic and monitoring in place and every output reviewed, then refined with the workflow owners.

• 90 days: at least one workflow live in production and used daily by Delivery, showing measurable reduction in manual work or faster turnaround against its baseline, and a prioritized roadmap for survey creation and fielding.

Education

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