Senior Forward Deployed Engineer - Wellness

Advatix

Northern (KY)

Hybrid

USD 170,000 - 205,000

Full time

13 hours ago
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Job summary

Advatix is seeking a Senior Forward Deployed Engineer - Wellness to lead the complete technical delivery lifecycle for wellness clients in a remote capacity. You will own engagements from pre-sales demonstrations through production deployment, translating client needs into AI-driven, production-ready solutions.

The role emphasizes architecture, data integration, and building scalable systems with strong client communication.

Qualifications

  • 5–15 years of professional software engineering experience.
  • Experience owning full technical delivery for clients (pre-sales, scoping, post-sale).
  • End-to-end production systems delivery, customer-facing.
  • Ability to design end-to-end architectures and diagrams.
  • Strong software architecture and data/ML pipeline experience.
  • Fluency in JavaScript/Node.js, TypeScript, Python; Next.js, React.
  • Excellent client-facing communication; autonomous decision-maker.

Responsibilities

  • Own full technical delivery lifecycle for wellness clients from pre-sales to production deployment.
  • Build demonstrations and translate requirements into production-ready solutions.
  • Architect AI agents and insight products using platform tools.
  • Integrate client data systems and design ETL/data ingestion pipelines.
  • Collaborate with client teams and internal product/engineering groups.
  • Produce system architectures, API designs, and fallback strategies.
  • Ship complex customer-facing software in production; make autonomous decisions.
  • Contribute learnings back to core platform to influence product direction.

Skills

End-to-end delivery
Client-facing communication
Production engineering
AI/ML pipelines
PySpark
ETL/ELT
Unstructured data handling
JavaScript/Node.js
TypeScript
Python
Next.js
React
System architecture
Cloud/native deployments
LLM systems
Prompt engineering
Observability

Tools

Platform tools (feature stores, MCP)

Job description

Location: , , United States,

Department: Information Technology, Type: Full Time

Role: Senior Forward Deployed Engineer - Wellness

Our Client is seeking a highly experienced and entrepreneurial Senior Forward Deployed Engineer to own the full technical delivery lifecycle for wellness clients - from pre-sales demonstrations through post-sale integration and production deployment. This role is ideal for an engineer-architect hybrid who can build AI-powered systems end-to-end while working directly with client technical teams and helping shape the core product through real-world customer requirements. The successful candidate will work with digital and location-based fitness providers to build production AI systems, integrate complex client data sources, and translate customer workflows into AI-orchestrated solutions. The ideal candidate will combine strong production engineering and software architecture experience with polished client-facing communication and an entrepreneurial, startup-minded approach.

Location: Remote

Job Type: Full-Time

Compensation: $170,000 - $205,000 per year (OTE: $190,000 - $240,000)

Equity: Competitive equity

Visa Sponsorship: Not available; U.S. Citizens and Green Card Holders only

Key Responsibilities

  • Own the full technical delivery lifecycle for wellness clients, including pre-sales demonstrations, requirements gathering, design sessions, implementation, testing, and production deployment.
  • Build customer-facing demonstrations and translate client requirements into production-ready technical solutions.
  • Architect and build AI agents and insight products using platform tools such as feature stores, knowledge bases, MCP, and agentic context packages.
  • Integrate client data systems, including CRMs and wellness applications.
  • Design and implement data ingestion processes, ETL pipelines, and solutions for heterogeneous data sources.
  • Collaborate directly with clients' data and technical teams through virtual technical working sessions.
  • Translate client workflows and requirements into production AI-orchestrated solutions.
  • Design complete system architectures and make technical integration decisions based on client requirements.
  • Articulate technical tradeoffs and develop architecture diagrams, API designs, and fallback strategies.
  • Build and deploy complex, customer-facing software systems in production.
  • Make autonomous technical decisions while operating across multiple aspects of client engagements.
  • Feed learnings from client deployments back into the core platform, spending approximately 10-20% of time influencing product direction through real-world client patterns.
  • Collaborate with internal product and engineering teams to incorporate customer learnings into reusable platform capabilities.
  • Work across engineering, architecture, data, AI, and client-facing responsibilities as required by each engagement.

Required Qualifications

  • Minimum 5 to 15 years of professional software engineering experience.
  • Experience owning full technical delivery for clients, including pre-sales, scoping, and post-sale integration.
  • Proven experience building and deploying customer-facing software systems end-to-end, through production engineering, solutions engineering, solutions architecture, or technical consulting.
  • Ability to design end-to-end system architectures and produce complete architecture diagrams.
  • Strong software architecture skills, including the ability to make integration decisions and articulate technical tradeoffs.
  • Experience building data and machine learning pipelines, including PySpark, ETL/ELT, unstructured data, document ingestion, and predictive models.
  • Fluency in modern programming languages and frameworks, including JavaScript/Node.js, TypeScript, Python, Next.js, and React.
  • Strong client-facing communication and professional presence.
  • Ability to run technical working sessions and present technical solutions to clients.
  • Production engineering experience shipping complex, customer-facing software systems.
  • Strong ability to work independently and make autonomous technical decisions.

Preferred Qualifications

  • Experience as a founding engineer, startup co-founder, startup CTO, or software engineer at a high-growth startup.
  • Experience in formal machine learning or internal data science work on healthcare-related projects.
  • Experience building LLM systems or AI agents, including:
  • Prompt engineering
  • Function calling
  • Structured output
  • Guardrails
  • Observability

Ideal Candidate Profile

The ideal candidate is an engineer-architect hybrid who has demonstrated the ability to own complex customer-facing technical engagements from initial requirements and pre-sales through production deployment. This person should be comfortable building production software, designing complete system architectures, integrating complex data sources, and working directly with customer technical teams. Strong client-facing communication and the ability to clearly explain technical decisions and tradeoffs are essential to the role. The ideal candidate will also have an entrepreneurial and startup-minded approach, with the ability to operate autonomously, take ownership across multiple areas, and contribute learnings from client engagements back into the core product.

Equal Employment Opportunity: In its recruiting and search practices, HRforGrowth does not discriminate on the basis of race, color, religion, national origin, age, marital status, physical or mental disability, sex, sexual orientation, gender, or gender identity, and welcomes applications from all qualified individuals. HRforGrowth evaluates and presents candidates to its clients without regard to any protected characteristic. HRforGrowth endeavors to advise the hiring organization to comply with all applicable federal, state, and local equal employment opportunity laws - including those enforced by the U.S. Equal Employment Opportunity Commission (EEOC) - in its hiring decisions, terms of employment, and workplace practices.

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