Software Development Engineer

                                       Software Development Engineer

About Cloudbyz
Cloudbyz delivers a Unified eClinical Platform built natively on Salesforce, purpose-built for mid-size
and top-20 pharma, biotech, and CROs. Our integrated suite — CTMS, eTMF, EDC, and AI-powered
clinical agents — eliminates data silos across the trial lifecycle and accelerates study start-up,
execution, and inspection readiness. With a rapidly growing customer base and an ambitious AI
roadmap, we are scaling our engineering organization to meet demand.

The Role
We are looking for a Software Development Engineer who thrives at the intersection of cloud
infrastructure and applied AI. You will design, build, and ship production-grade AI solutions that power
the next generation of Cloudbyz clinical agents — including our eTMF AI Agent, Enrollment
Intelligence, and Auto-Query automation products. You will work directly with product, clinical
informatics, and platform teams to translate complex trial workflows into intelligent, scalable systems
on AWS or Azure.

Core Responsibilities
• Architect and deliver end-to-end AI/ML solutions from proof-of-concept to production on AWS
or Azure
• Build and maintain LLM-powered agents for clinical document classification, auto-query
generation, risk-based monitoring, and eTMF QC workflows
• Develop RAG pipelines, vector-search systems, and knowledge graphs over clinical trial
document corpora
• Integrate Cloudbyz platform with Salesforce APIs, Einstein AI, and external eClinical systems
(Veeva Vault, Medidata, Oracle)
• Design cloud-native microservices and serverless event pipelines (AWS Lambda / Azure
Functions / Kafka)
• Build and own CI/CD pipelines with automated testing, model performance monitoring, and
observability
• Participate in architecture reviews and drive engineering best practices across the team
• Contribute to the AI product roadmap by prototyping novel capabilities aligned with clinical
operations needs

Requirements
• 4+ years software engineering; 2+ years in
AI/ML delivery
• Proficiency in Python; TypeScript or Java
a strong plus
• Hands-on AWS (Bedrock, SageMaker,
Lambda, S3, ECS) or Azure (OpenAI
Service, ML Studio, AKS)
• Experience with LLM orchestration:
LangChain, LlamaIndex, or Semantic
Kernel
• Vector database experience: Pinecone,
Weaviate, pgvector
• Strong REST API design and event-driven
architecture patterns
• Track record shipping AI features in
regulated or data-sensitive industries
• Familiarity with Salesforce platform and/or
Apex is a significant advantage
• Experience building agentic or multi-step
reasoning workflows
• Strong written communication; comfort
working directly with clinical or domain
SMEs

Nice to Have
• Prior experience in life sciences, pharma, biotech, or clinical trials software
• Knowledge of eTMF, CTMS, EDC, or ICH E6 GCP document standards
• AWS Certified ML Specialty or Azure AI Engineer Associate certification
• Contributions to open-source AI/ML projects
• Experience with Veeva Vault or Medidata Rave integrations

Technology Stack
Python TypeScript / Node.js AWS Bedrock Azure OpenAI Service
SageMaker Azure ML Studio LangChain LlamaIndex
Pinecone / pgvector Salesforce / Apex Kafka / Event Bus Docker / Kubernetes
Terraform / IaC FastAPI MLflow GitHub Actions