Embedded Production AI Engineer – Pharma Deployments

Axtria - Ingenious Insights; Boston (MA); On-site; USD 180,000 - 280,000; Full time

Job summary

Axtria - Ingenious Insights seeks Forward Deployment Engineers to build and deploy production AI for pharma clients. You will lead multi-agent AI architectures, own client-facing delivery, and mentor engineers in fast-paced engagements.

Candidates bring 10+ years in engineering/data/AI within life sciences, with production deployments and deep pharma domain knowledge. Strong cloud, Python, and SQL skills are essential.

Qualifications

• 10+ years in engineering, data, or AI with pharma exposure.
• Pharma domain experience mandatory with commercial/clinical depth.
• Production AI engineering with real deployments (not PoCs).
• Strong foundations in Python, SQL, cloud infra, and API design.
• Fluency across pharma AI platforms (Databricks, Snowflake, AWS Bedrock, Claude/Anthropic).

Responsibilities

• Embed directly within pharma client organizations, owning end-to-end deployment of production AI systems on client infrastructure.
• Lead the technical workstream and guide teams of engineers under your ownership.
• Manage senior client relationships: scope problems, present trade-offs, defend designs to executives.
• Architect multi-agent AI systems for pharma environments, including orchestration and memory architectures.
• Contribute to Axtria's library of deployment patterns and mentor junior FDEs.

Skills

Pharma domain experience

Production AI engineering

Python

SQL

Cloud infrastructure

Databricks

Snowflake

AWS Bedrock

Claude API

Client-facing leadership

Delivery leadership

Tools

Databricks Delta Lake

Snowpark

Genie

Claude API

Anthropic API

AWS SageMaker

Job description

Axtria - Ingenious Insights seeks Forward Deployment Engineers to build and deploy production AI for pharma clients. You will lead multi-agent AI architectures, own client-facing delivery, and mentor engineers in fast-paced engagements.

Candidates bring 10+ years in engineering/data/AI within life sciences, with production deployments and deep pharma domain knowledge. Strong cloud, Python, and SQL skills are essential.