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Forward Deployment Engineer – AI (Pharma)

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Onsite

Forward Deployment Engineer – AI (Pharma)

Nityo Infotech

Forward Deployment Engineer – AI (Pharma)

Skills

Google Cloud PlatformData EngineeringPythonSnowflakeDatabricksMachine LearningAIAWSOracleNLP / Natural Language ProcessingComplianceTerraformAzure

1 month ago

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Important information


Contract type:

Freelance / Contract

Location:

Barcelona, Spain

Work mode:

Onsite

Published on:

24 September 2026

What they need


Role: Forward Deployment Engineer – AI (Pharma)

Client: Altimetrik

Duration: 1-year fixed-term contract to long-term

Location: Barcelona, Spain(Hybrid, 2 days a week)

Salary: Market Range

Forward Deployment Engineer – AI (Pharma)

About the Role

We are looking for a Forward Deployment Engineer (FDE) to sit at the intersection of AI engineering and customer success. You will work directly with pharma clients to deploy, integrate, and scale AI-powered solutions — translating complex technical capabilities into real-world workflows. This is a hands-on, client-facing engineering role where you own outcomes, not just deliverables.

What You'll Do

  • Partner with pharma clients from pilot to production — leading technical onboarding, integration, and go-live

  • Build and maintain API integrations between AI platforms and client systems (EHR, CTMS, regulatory, lab, and commercial sytems)

  • Deploy AI/ML models and inference services on cloud infrastructure (AWS, Azure, or GCP), ensuring reliability, security, and scalability

  • Translate domain-specific pharma workflows (clinical trials, pharmacovigilance, regulatory submissions, drug discovery) into technical requirements

  • Debug integration issues in production, triage model behavior, and coordinate with internal engineering teams on fixes

  • Develop reusable reference architectures, integration playbooks, and technical documentation

  • Act as a trusted technical advisor to client engineering and IT teams

  • Surface product feedback from the field to inform the roadmap

What You Bring

Engineering

  • 4+ years of software or integration engineering experience

  • Strong proficiency in Python; experience with REST API design, OAuth, and webhook integrations

  • Hands-on cloud deployment experience (AWS, Azure, or GCP) — containers, serverless, IAM, networking

  • Familiarity with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering basics

  • Hands-on data engineering experience with Snowflake or Databricks — data pipelines, transformations, and working with large structured/unstructured datasets

  • Experience with CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation, or similar)

Domain

  • Working knowledge of the pharmaceutical value chain — clinical development, regulatory affairs (FDA/EMA), pharmacovigilance, or commercial operations

  • Familiarity with pharma data standards (CDISC, HL7/FHIR, MedDRA) is a strong plus

  • Understanding of pharma compliance and data privacy requirements (21 CFR Part 11, GxP, HIPAA)

Soft Skills

  • Comfortable in ambiguous, fast-moving client environments

  • Strong communicator — able to explain technical concepts to non-technical stakeholders

  • Self-directed; can manage multiple client engagements simultaneously

Nice to Have(Not required)

  • Experience with RAG pipelines, vector databases, or document AI (OCR, NLP)

  • Background in a pharma/biotech company or a consulting firm serving the life sciences sector

  • Familiarity with platforms like Veeva, Medidata, or Oracle Health Sciences

What Success Looks Like

In the first 30 days, you're embedded with a client team and have shipped at least one integration. In 90 days, you're running deployments independently and have become the go-to technical resource for your accounts.

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