Senior AI Engineer, Forward Deployed
About The Position
Komodo Health is seeking a Senior AI Engineer, Forward Deployed, to join their team. This role is crucial for deploying and scaling Komodo's AI-native product, Marmot, within complex enterprise healthcare environments. The Forward Deployed Engineering team operates at the intersection of Engineering and Revenue, responsible for building, deploying, and owning the outcome of Marmot in production within customer infrastructure, adhering to strict compliance requirements and handling diverse integrations. The mission of the role is to own end-to-end delivery for technically demanding customer engagements, from solution architecture to deployment within customer clouds and data infrastructure. This is a deeply technical role requiring production code writing, cloud-native deployment pattern design, integration building, MCP server development, and debugging in controlled customer environments. The engineer will translate customer requirements into scalable solutions, communicate with stakeholders, and ensure transparency on project status. Engineers on this team ship real solutions under real constraints and see them run in production.
Requirements
- 7+ years of software engineering experience, including at least 2 years shipping production agentic AI systems and 3+ years owning cloud infrastructure.
- Production-grade agentic AI: multi-agent workflows and LLM-powered tools in production. You know what breaks and why. LangGraph, Strands, CrewAI, or equivalent in your regular toolkit.
- AWS + Terraform: you write IaC, understand VPC networking and IAM, and can stand up an isolated single-tenant deployment in a customer's environment.
- Security and networking judgment, especially in enterprise or regulated environments. You understand data isolation, customer security requirements, and compliance considerations such as SOC 2, BAA, HIPAA, or TPA — and you design with those constraints in mind.
- Strong application engineering skills at system scale, including production Python, async service patterns, API development, and building software other teams or businesses depend on.
- Data platform experience with tools like Databricks, Delta Lake, Snowflake, S3, or similar systems. You can debug integration failures, optimize performance, and design pipelines that are reliable under production load.
- MCP server development or equivalent experience building integration surfaces for AI systems. Core to the role.
- Customer-facing technical leadership, including leading architecture discussions with senior customer engineers, explaining trade-offs clearly, and driving technical alignment without needing to hand off the conversation.
- Comfort operating across ambiguity, with the ability to stitch together solutions 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 Haves
- 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.
- Experience with API gateway or service mesh patterns used for AI tool integration.
- Contributions to shared platform infrastructure, including code committed to shared repos, participation in architecture reviews, or tooling that other engineers depend on.
- Experience deploying in regulated environments with data residency, audit logging, or multi-party data access constraints.
Responsibilities
- Design, build, and deploy AI solutions inside customer environments, adapting Komodo’s platform to fit their cloud infrastructure, systems, data contracts, and compliance requirements.
- Build MCP servers, agentic workflows, and custom integrations that close platform gaps and help customers get to value quickly.
- 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, surfacing risks early, and building trust over time.
- Serve as a field signal to Core Platform by translating deployment friction into roadmap input and participating in architecture governance.
- Help build the FDE playbook through reusable patterns, deployment templates, and engineering standards the team can scale.
Benefits
- comprehensive health, dental, and vision insurance
- flexible time off and holidays
- 401(k) with company match
- disability insurance and life insurance
- leaves of absence in accordance with applicable state and local laws and regulations and company policy
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
