We’re looking for a senior engineer who can take Vi’s AI agent capabilities and make them work in production. You’ll build and ship intelligent AI agents for Wellness clients — owning everything from data ingestion and CRM integration to real-time agent infrastructure. This is a client-facing role: you work closely with enterprise customers to understand their workflows, then you build AI orchestrated workflows that automate them.
You’re comfortable with databases, data pipelines, AI/ML tooling, agent configuration, and the messy realities of integrating with healthcare data systems. You ship fast, you think in products, and you don’t wait for specs.
What you'll do
Build and deploy AI agents for Wellness clients, end-to-end.
Translate client workflows into real agent workflow design. Run technical sessions with clients' clinical, IT, and ops teams; converting needs into prompts, tools, retrieval shapes, and vector stores.
Integrate with client data systems including CRMs and build the ingestion pipelines to support them.
Write the production stack - agent runtime, routing, orchestration, evals; help build out the ML side in Python (training, embeddings, model registry); compose declarative guardrails & integrations within workflows.
Design and maintain databases (relational and caching layers) that support both real-time agent operations and compliance audit trails.
Codify per-client configuration patterns into reusable components so each new client onboards faster than the last.
Collaborate with product, account management, and platform engineering to translate field learnings into platform improvements.
What We’re Looking For
5+ years in a production engineering role shipping customer-facing software. Solutions engineering or consulting backgrounds qualify if you were writing and deploying production code, not just scoping it.
Fluency in wide range of programming languages (Javascript/Node, Typescript, Python, etc)
Experience building and operating real-time systems: WebSockets, streaming media, event-driven architectures, or high-throughput API services.
Production integration work with CRM platforms (Salesforce, HubSpot, or similar) or data warehouse/lake connectors (Snowflake, Databricks, S3).
Have built retrieval and ingestion paths that feed agents reliable context with correct guardrails & caching in place.
Working knowledge of data engineering patterns: ETL/ELT pipelines, data quality checks, ingestion from heterogeneous sources.
Comfort with cloud infrastructure (AWS, GCP): containers, CI/CD, monitoring, and basic security practices.
Strong client-facing communication: you can run a technical working session with a customer’s IT team and translate what you learn into engineering decisions.
Startup disposition: you build, you ship, you fix what breaks. Low ego, high agency.
Nice to have
Voice or telephony infrastructure experience: building or operating real-time call systems at scale.
LLM orchestration and agentic system design: prompt engineering, function calling, structured output, guardrails.
Experience with workflow engines, rules engines, or state machine architectures.
Product sensibility: you think about user experience, not just system architecture. You’ve influenced product direction through technical insight.