# Senior AI Engineer, Forward Deployed

**Company:** [Komodo Health](https://hotfix.jobs/companies/komodo-health)
**Location:** Remote
**Role:** Solutions Architecture
**Salary:** $191k – $253k/yr
**Experience:** 7+ years
**Skills:** Python, AWS, Terraform, Databricks, Delta Lake, Snowflake, S3, LangGraph, Langsmith, HIPAA
**Posted:** 2026-05-28

> Senior AI Engineer deploying and owning production AI-native solutions (MCP servers, agentic workflows) inside customer cloud environments with strict compliance requirements.

## Job Description

## Responsibilities

- Design, build, and deploy AI-native solutions inside customer environments, including MCP servers, agentic workflows, and custom integrations that adapt Komodo’s platform to each customer’s cloud infrastructure, systems, data contracts, and compliance requirements.
- Own the infrastructure layer for customer deployments, including Terraform-managed AWS environments, VPC networking, IAM, security controls, and data isolation requirements.
- Work with data at scale across tools like Databricks, Delta Lake, Snowflake, and S3 — debugging pipeline failures, optimizing performance, and building integrations that hold up in production.
- Drive day-to-day technical engagement with customer stakeholders by scoping work, communicating progress, explaining tradeoffs, surfacing risks early, and building trust over time.
- Turn field learnings into reusable FDE patterns, deployment templates, engineering standards, and roadmap input for Core Platform and architecture governance.

## Requirements

- 7+ years of software engineering experience, with a track record of building and owning systems that run in production.
- Hands-on experience building LLM-powered applications, agentic workflows, or AI tools beyond prototypes.
- Strong AWS and Terraform experience, including VPC networking, IAM, security controls, and standing up reliable customer or single-tenant environments.
- Strong Python skills, experience with APIs, async service patterns, and building software that other teams, customers, or businesses depend on.
- Experience working with large-scale data systems such as Databricks, Delta Lake, Snowflake, S3, or similar platforms, including debugging failures and improving performance or reliability.
- Comfort designing for data isolation, customer security requirements, and regulated environments with constraints such as SOC 2, BAA, HIPAA, or similar considerations.
- Experience building integration surfaces for AI systems, including MCP servers or equivalent patterns that connect tools, data, and workflows.
- Ability to lead technical conversations with customer engineers and senior stakeholders, explain tradeoffs clearly, drive alignment, and build trust.
- Ability to work across infrastructure, application, data, and AI layers, find a path when one does not already exist, and deliver on what you commit to.

## Nice to Have

- Experience with LLM evaluation frameworks in production, such as LangSmith, Braintrust, Ragas, or equivalent tools.
- Familiarity with healthcare or life sciences data, including IQVIA data structures, pharma customer workflows, payer data contracts, or similar data environments.

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