# Principal AI Engineer > Velsera · Pune, India (Hybrid) · Full-time · Posted 2026-05-18 **Workplace:** hybrid **Department:** Technology ## Description **About Velsera** Medicine moves too slow. At Velsera, we are changing that. Velsera was formed in 2023 through the shared vision of Seven Bridges and Pierian, with a mission to accelerate the discovery, development, and delivery of life-changing insights. Velsera provides software and professional services for: - AI-powered multimodal data harmonization and analytics for drug discovery and development - IVD development, validation, and regulatory approval - Clinical NGS interpretation, reporting, and adoption With our headquarters in Boston, MA, we are growing and expanding our teams located in different countries! **About the role**  Velsera’s Seven Bridges Platform is used by biomedical researchers and pharma teams to run reproducible analyses in regulated environments. We’re adding an AI platform layer to Seven Bridges—model invocation, self-hosted LLM serving, governance, and workflow integration—without compromising security, auditability, or interoperability.  You’ll report to the CTO as a senior individual contributor. You’ll design and ship production AI systems that meet compliance needs (e.g., FedRAMP, HIPAA/21 CFR Part 11/GxP), work across AWS, Azure and GCP, and set the technical direction for what will grow into an AI platform team.  - Build a governed model access layer (self-hosted open-weight models, cloud-managed models such as Bedrock, and customer-supplied models)  - Integrate AI capabilities into platform experiences (batch workflows and interactive sessions)  - Establish patterns for evaluation, versioning, approvals, audit trails, and safe rollout  - Partner with product, security/compliance, and scientific teams to introduce AI-native architectures and ship capabilities customers can adopt  This role is a fit if: - You want to build the platform layer (serving, governance, integrations)—not do model research or purely prompt engineering.  - You’re excited about shipping in regulated environments where auditability and access control are core requirements.  - You like working inside an existing production platform and improving it without breaking what customers rely on.  **What will you do?** - A production-ready, compliant AI/LLM serving and invocation layer for Seven Bridges (multi-tenant, auditable, and secure)  - A clear governance workflow for models (intake, evaluation, approval, versioning, deprecation) that works for regulated customers  - A first set of “AI in the platform” features shipped end-to-end (e.g., assisted validation/compliance tooling, cost/error assistance, workflow helpers)  - Integration patterns that keep workflows reproducible and standards-aligned (CWL/WDL/Nextflow and GA4GH-friendly where applicable)  - Operational readiness: monitoring, incident playbooks, and measurable SLOs for key AI services  **How we build (and what we’ll expect you to optimize for):** You’ll make trade-offs in a platform that’s standards-driven, multi-cloud, and compliance-heavy. A few things matter a lot here:  - Standards and interoperability. Prefer open standards and clean interfaces over one-off integrations.  - Multi-cloud reality. Design for AWS and GCP; avoid hard dependencies on a single provider’s AI stack.  - Security/auditability by default. Access control, logging, traceability, and data governance are part of the design—not add-ons.  - Reproducibility. AI features should fit into workflows that need to be repeatable and explainable. ## Requirements **What do you bring to the table?** - 7+ years in software engineering, including 3+ years shipping AI/ML systems to production  - Strong Python, plus one of Java/Go/TypeScript; comfortable in a polyglot codebase and production code reviews  - Hands-on experience with secure cloud architectures on AWS (network isolation, IAM boundaries, private connectivity, audit logging)  - Experience operating or integrating model serving across options: self-hosted open-weight models, managed model APIs (e.g., Bedrock), and customer-provided models  - MLOps experience using AWS Bedrock, Google Vertex AI or similar  - Built governance for ML/LLM systems (evaluation, versioning, approvals, rollout/rollback, deprecation)  - Comfortable designing for regulated environments (FedRAMP, HIPAA, 21 CFR Part 11, GxP, or similar)  - Experience with RAG and LLM tool-use/agentic patterns beyond prototypes  - Clear written communication for mixed audiences (engineering, product, security/compliance, and scientists)  **Nice-to-have:** - Experience in genomics, biomedical data, or life sciences platforms  - Integrating AI capabilities into workflow engines (CWL/WDL/Nextflow) or similar orchestration systems  - Familiarity with GA4GH standards (e.g., WES/DRS/TRS) and/or clinical data models (FHIR/OMOP)  - Production experience on both AWS and GCP; comfort making pragmatic multi-cloud trade-offs ## Benefits - Flexible Work & Time Off - Embrace hybrid work models and enjoy the freedom of unlimited paid time off to support work-life balance. - Health & Well-being - Access comprehensive group medical and life insurance coverage, along with a 24/7 Employee Assistance Program (EAP) for mental health and wellness support. - Growth & Learning - Fuel your professional journey with continuous learning and development programs designed to help you upskill and grow. - Engaging & Fun Work Culture - Experience a vibrant workplace with team events, celebrations, and engaging activities that make every workday enjoyable. - & Many More... ## Apply [Apply at Velsera](https://apply.workable.com/velsera/j/AA6D79B1FD/apply) --- Powered by [Workable](https://www.workable.com)