23 hours ago
Hyderābād, IndiaStaff+
Responsibilities
- Design, deploy, and scale multi-agent orchestration systems and autonomous workflows.
- Build and optimize advanced retrieval-augmented generation pipelines over structured and unstructured regulatory datasets.
- Implement state management, short- and long-term memory, self-correction, reflection loops, evaluations, observability, and guardrails for AI agent networks.
- Optimize inference cost, latency, throughput, token usage, performance, and system reliability.
- Implement access controls, encryption, authentication, and prompt-injection mitigation across LLM workflows.
- Design, build, and maintain scalable data transformation, ingestion, processing, and integration pipelines.
- Integrate diverse data sources across complex regulatory data ecosystems while maintaining secure cross-platform data flows.
- Own large-scale data engineering initiatives and independently manage projects from inception through deployment.
- Partner with business units and data scientists to translate data requirements into technical solutions.
- Mentor engineers, document reusable agent patterns and engineering components, share knowledge, and align development plans with global strategy.
- Deliver solutions that comply with GxP frameworks, data integrity principles, computer systems validation, and regulatory and clinical-development milestones.
Requirements
- Bachelor’s or master’s degree in computer science, software engineering, or a related technical field.
- 10+ years of professional software development experience.
- Strong full-stack and backend expertise in Python, R, FastAPI, and modern cloud architectures.
- Hands-on experience with LLM frameworks, agentic architectures, advanced RAG pipelines, prompt engineering, and vector stores.
- Experience with AWS, Terraform, multi-architecture builds, structured logging, distributed tracing, and metrics or monitoring.
- Extensive pharma or biotech experience building data pipelines in GxP-regulated environments, including GCP, GMP, GVP, data integrity, and CSV requirements.
- Understanding of regulatory data standards, Regulatory Information Management ecosystems, electronic submission frameworks such as eCTD Modules 1–5, ICH guidelines, and 21 CFR Part 11.
- Ability to architect traceable, audit-ready, compliant AI agent outputs and scalable solutions for regulated R&D environments.
- Strong communication, collaboration, mentoring, stakeholder engagement, ownership, and complex problem-solving skills.
- Familiarity with cloud services and DevOps practices is preferred.
Categories
AI ApplicationsData Engineering
About Roche
Roche is a Swiss healthcare company that develops and sells prescription pharmaceuticals and in vitro diagnostic systems for hospitals, laboratories, and clinicians. Its business spans two core divisions —Pharmaceuticals and Diagnostics—with strengths in oncology, immunology, neuroscience, infectious diseases, and diabetes care. Founded in 1896 and headquartered in Basel, Switzerland, Roche also advances personalized healthcare by pairing therapies with companion diagnostics.