Job Description

Job Requirements

Key Responsibilities

#

Agile Delivery Leadership

Champion

Scrum, Kanban, and SAFe

principles while adapting them to suit product maturity and regulatory requirements. Facilitate

sprint planning, backlog refinement, daily stand-ups, sprint reviews, and retrospectives

with technical and business stakeholders. Drive

incremental delivery

and ensure teams deliver

working, high-quality software

on predictable timelines. Remove delivery blockers proactively, from technical dependencies to cross-team alignment issues.
#

Technical Engagement

Understand

system architecture, AI model lifecycle, MLOps pipelines

, and

data flows

to better facilitate technical discussions. Collaborate with

Tech Leads, Data Scientists, ML Engineers, and DevOps teams

to ensure sprint commitments are technically achievable. Track

code quality, automated test coverage, CI/CD health

, and

cloud infrastructure readiness

as part of delivery metrics. Ensure

data privacy, security, and regulatory compliance

are integrated into delivery workflows.
#

Stakeholder & Product Alignment

Partner with

Product Owners, Clinical SMEs, Data Science, Data Engineering and Customer Success

to ensure backlog priorities align with business outcomes and value driven Balance innovation speed with healthcare/pharma compliance requirements (HIPAA, GDPR, FDA, GxP). Ensure transparent and regular communication of

progress, risks, and dependencies

to leadership and stakeholders.
#

Metrics & Continuous Improvement

Establish and monitor

KPIs

such as sprint predictability, sprint metrics such as burn rate, lead time, defect leakage, and deployment frequency. Drive

retrospective outcomes

into actionable improvements for team efficiency and product quality. Introduce

process automation, backlog grooming discipline, and release readiness checklists

to optimize delivery.

Work Experience

Required Qualifications

8+ years

in software delivery roles, with

5+ years as a Scrum Master

or Agile Delivery Lead. Proven track record in

SaaS product delivery

, preferably with

AI/ML-powered platforms

. Strong technical foundation in

cloud-native architectures (AWS/Azure/GCP)

,

APIs

,

microservices

, and

data engineering workflows

. Excellent

servant-leadership, facilitation, and conflict resolution

skills

Proactive thinker with ability to influence stakeholder based on business objectives and value delivery

Strong analytical ability to interpret technical and business metrics for decision-making. Familiarity with

generative AI

,

NLP

, and

predictive analytics

in healthcare contexts. Familiarity with

ML model development

,

MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI)

, and

data governance

Experience in

healthcare and/or pharma software

, with strong understanding of EHR/EMR health records and

HIPAA, GDPR, GxP, and FDA 21 CFR Part 11

compliance. * Understanding of

clinical trial systems

and/or

RWE (Real World Evidence) platforms

, or

drug discovery pipelines

.