Principal AI Engineer

Velsera

Maharashtra

Hybrid

INR 1,500,000 - 2,500,000

Full time

14 days+

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Benefits offered by this job

Unlimited paid time off
Comprehensive medical insurance
Continuous learning programs
Engaging work culture

Job summary

Velsera is seeking a seasoned software engineer to lead the development of an AI platform layer for its Seven Bridges Platform. This role involves designing production-ready AI systems that meet strict compliance needs, collaborating with multiple teams, and enhancing platform capabilities while maintaining security and interoperability.

The ideal candidate will have extensive experience in software engineering, particularly in AI/ML systems, and proficiency in cloud environments such as AWS, GCP, and Azure. The position promotes a culture of continuous learning and work-life balance.

Qualifications

  • 7+ years in software engineering, including 3+ years shipping AI/ML systems to production.
  • Strong knowledge of Python, plus one of Java/Go/TypeScript.
  • Hands-on experience with secure cloud architectures on AWS.

Responsibilities

  • Design production-ready AI systems for the Seven Bridges platform.
  • Build a governed model access layer and integrate AI capabilities.
  • Establish evaluation, versioning, and governance workflows.

Skills

Software Engineering
Python
Cloud Architectures
MLOps
Regulatory Compliance

Tools

AWS
GCP
Azure

Job description

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 is 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
  • 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
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