1 day ago

Senior Forward Deployed Engineer, AI Infrastructure & Deployments

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Build and deploy AI-native solutions inside complex enterprise healthcare environments, owning end-to-end delivery from solution architecture through production rollouts. Write production code, design cloud-native deployment patterns, develop MCP servers and integrations, and debug issues in customer environments. Partner closely with Engineering, Product, Sales, and customer stakeholders, translating requirements into scalable outcomes while balancing speed with compliance and production rigor.

Location: Chicago, New York, San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design, build, and deploy AI-native solutions inside customer environments, including MCP servers, agentic workflows, and custom integrations for cloud, data contracts, and compliance needs.
•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 Databricks, Delta Lake, Snowflake, and S3—debugging pipeline failures, optimizing performance, and building production-ready integrations.
•Engage daily with customer technical stakeholders by scoping work, communicating progress, explaining tradeoffs, surfacing risks early, and building trust.
•Convert field learnings into reusable FDE patterns, deployment templates, engineering standards, and roadmap input for core platform and architecture governance.

Travel: Low travel

Pay and Benefits

Perks:Health InsuranceDentalVision401kPaid LeaveDisability InsuranceLife Insurance

Key Requirements

•7+ years of software engineering experience building and owning systems running in production.
•Hands-on experience building LLM-powered applications, agentic workflows, or AI tools beyond prototypes (e.g., LangGraph, Strands, CrewAI).
•Strong AWS and Terraform experience, including VPC networking, IAM, security controls, and standing up reliable customer or single-tenant environments.
•Strong Python skills with APIs, async service patterns, and building software other teams/customers depend on.
•Experience with large-scale data systems such as Databricks, Delta Lake, Snowflake, and S3, including debugging failures and improving performance or reliability.

Experience:7+ yearsHealthcareAILLMAgentic AICloudData infrastructure

Skills:CommunicationStakeholder managementRisk managementTradeoff decision-makingWorking in ambiguity

Languages:English

Tech Stack:AILLMMCP GatewayMCP serversTerraformAWSVPCIAMPythonDatabricksDelta LakeSnowflakeS3LangGraphStrandsCrewAILangSmithBraintrustRagasSOC 2

Company Brief

Komodo Health

Provides a healthcare data platform that combines medical and administrative datasets with analytics to help life sciences companies, payers, and providers measure patient journeys, optimize research, and improve outcomes.

Industry: HealthTech

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: New York, United States

Founded: 2014

Website LinkedIn

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Komodo Health

1 day ago

Senior Forward Deployed Engineer, AI Infrastructure & Deployments

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: Chicago, New York, San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design, build, and deploy AI-native solutions inside customer environments, including MCP servers, agentic workflows, and custom integrations for cloud, data contracts, and compliance needs.
•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 Databricks, Delta Lake, Snowflake, and S3—debugging pipeline failures, optimizing performance, and building production-ready integrations.
•Engage daily with customer technical stakeholders by scoping work, communicating progress, explaining tradeoffs, surfacing risks early, and building trust.
•Convert field learnings into reusable FDE patterns, deployment templates, engineering standards, and roadmap input for core platform and architecture governance.

Travel: Low travel

Pay and Benefits

Perks:Health InsuranceDentalVision401kPaid LeaveDisability InsuranceLife Insurance

Key Requirements

•7+ years of software engineering experience building and owning systems running in production.
•Hands-on experience building LLM-powered applications, agentic workflows, or AI tools beyond prototypes (e.g., LangGraph, Strands, CrewAI).
•Strong AWS and Terraform experience, including VPC networking, IAM, security controls, and standing up reliable customer or single-tenant environments.
•Strong Python skills with APIs, async service patterns, and building software other teams/customers depend on.
•Experience with large-scale data systems such as Databricks, Delta Lake, Snowflake, and S3, including debugging failures and improving performance or reliability.

Experience:7+ yearsHealthcareAILLMAgentic AICloudData infrastructure

Skills:CommunicationStakeholder managementRisk managementTradeoff decision-makingWorking in ambiguity

Languages:English

Tech Stack:AILLMMCP GatewayMCP serversTerraformAWSVPCIAMPythonDatabricksDelta LakeSnowflakeS3LangGraphStrandsCrewAILangSmithBraintrustRagasSOC 2

Company Brief

Komodo Health

Industry: HealthTech

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: New York, United States

Founded: 2014

Website LinkedIn