We’re building the next generation of conversational voice and video AI for life sciences—intelligent with 100% regulatory compliance. Our AI medical experts help pharma teams engage doctors, support patients, and unlock insights faster than ever before. We’ve just raised our seed, signed our first customers, and are scaling fast. If you're excited about building real-world AI in an early stage startup and shape not just our product, but our identity and culture —this is your moment.
We move like owners.
Everyone at SynthioLabs has the autonomy and the responsibility to drive projects, challenge decisions, and push things forward. We don’t wait for permission. If you see a gap, you fill it. If you see a better way, you try it.
We ask “why” until we get to the root.
We explore new ideas, research papers, every single edge case and anything that sharpens our understanding.
We use AI like a second brain.
From writing code to writing docs, debugging flows to exploring new ideas, AI is part of our daily rhythm. Everyone here gets hands-on with the tools, learns how to prompt better, and treats AI as a teammate.
Overview
We are looking for a
Forward Deployed Engineer – Tech
to work at the intersection of
AI engineering, product deployment, and client engagement
. This role partners closely with customers and internal engineering teams to build, deploy, and operationalize AI-powered applications in real-world commercial environments.
You will combine
software engineering, AI application development, and product thinking
to translate complex business workflows into scalable AI systems. The role requires hands-on experience building
AI-enabled applications, integrating LLMs, and deploying production-grade infrastructure
, along with the ability to work directly with clients to implement solutions.
This position is ideal for engineers who enjoy
building quickly, solving ambiguous problems, working directly with customers, and shipping production systems that power real-world AI applications.
Responsibilities
AI Application Development
Build AI-powered applications using
LLMs, APIs, and modern AI frameworks
.**
- Design and implement workflows that combine
structured enterprise data with generative AI capabilities**.
Develop prototypes and production-ready systems that support real-world client deployments.
Infrastructure and Deployment
Design and manage infrastructure required to deploy AI applications reliably and securely.
Work with cloud environments to support
model hosting, data pipelines, and scalable application deployment
.
Implement monitoring, performance optimization, and system reliability practices.
Client-Facing AI Application Deployment
Work directly with clients and internal teams to implement and customize AI-powered applications for commercial and operational use cases.
Translate client workflows and requirements into scalable AI-driven software solutions.
Serve as the technical bridge between client teams, product, and engineering.
Product Collaboration
Partner with product and engineering teams to translate client needs into scalable platform capabilities.
Contribute to the development of reusable infrastructure and components for AI application deployment.
Support rapid prototyping and experimentation to accelerate product development.
###
Stakeholder Communication
Work closely with client technical teams to integrate AI solutions into their environments.
Explain technical architectures and deployment approaches to both technical and non-technical stakeholders.
Collaborate cross-functionally across product, engineering, and founders directly.
##
Education
Bachelor’s or Master’s degree in
Computer Science, Engineering, AI/ML, or a related technical field
.
Experience
0–3 years of experience in
software engineering, AI engineering, or machine learning systems development
.**
- Experience building applications using
Python, JavaScript, or similar languages
.
- Experience working with
LLM APIs, AI frameworks, or generative AI tooling
is preferred.
- Familiarity with
cloud infrastructure and application deployment** is preferred.
###
Technical Skills
Experience building and deploying
production software systems
.**
- Familiarity with
AI application development frameworks, APIs, and model integration
.
- Understanding of
software architecture, system design, and backend services
.
- Experience with
containerization, APIs, or cloud platforms** is a plus.
###
Domain Knowledge
Exposure to
pharmaceutical or healthcare technology environments
is a plus but not required.**
- Interest in applying AI systems to
life sciences commercial and operational workflows** is preferred.
###
Skills
Strong engineering and problem-solving abilities.
Ability to build and iterate quickly in ambiguous environments.
Comfort working in client-facing technical roles.
Strong collaboration across engineering, product, and customer teams.
##
What Makes This Role Unique
Work directly with clients to
deploy real AI systems into production environments
.**
- Build
AI-powered applications rather than just models or prototypes
.
- Blend
software engineering, AI infrastructure, and customer-facing problem solving
.
- Help build the next generation of
AI-native platforms for life sciences.**