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- Experience: 12–20 years
- Salary Range: 30LPA – 50LPA
- Key Skills: Software Engineering, People and Performance Management, AI/Agentic AI, Cloud, and DevOps.
- Work Arrangement: Hybrid (3 days in office, HSR Bangalore).
Required Qualification
s▸ 12+ years of progressive software engineering experience, with at least 3 years managing multiple teams simultaneously
.▸ Demonstrated track record of shipping complex, distributed systems in a fast-paced produc
tenvironment
.▸ Hands-on or deep architectural exposure to AI/ML systems and/or Agentic AI frameworks (LangChain, AutoGen, CrewAI, or equivalent)
.▸ Experience with data analytics platforms, data warehousing, and BI tooling (e.g., dbt, Snowflake
,Spark, Databricks, Looker, or similar)
.▸ Strong proficiency in at least one major cloud provider (AWS, Azure, or GCP) and familiarity wit
hDevOps/MLOps practices — CI/CD pipelines, containerization (Docker/Kubernetes), an
dinfrastructure-as-code (Terraform or equivalent)
.▸ Excellent communication skills — able to influence at all levels from IC engineers to C-suit
eexecutives
.▸ Experience leading through ambiguity, organizational change, and rapid growth
.
Preferred Qualificatio
ns▸ Experience in Healthcare IT, Digital Health, or Life Sciences — including familiarity with HIPA
A,HITECH, and interoperability standards (HL7, FHIR, SMART on FHIR
).▸ Background in systems integration — EHR/EMR integrations, API gateways, EDI, or enterpri
semiddleware (e.g., MuleSoft, Azure API Management, AWS API Gateway
).▸ Experience building or scaling AI-driven clinical decision support, NLP pipelines, or predictive analytics product
s.▸ Exposure to regulatory compliance frameworks relevant to healthcare software (FDA SaMD, SOC 2,ISO 27001
).▸ An engineering background (BS/MS in CS, CE, or related field preferred, but not required wi
thequivalent experience
).Job ID: 150631661
Skills:
Devops, automation, Microsoft Technologies, Delivery Excellence, Project Governance, Agile delivery methodologies, financial management, program management, modern software engineering practices, AI adoption
Skills:
privacy compliance , Gdpr, Apis, Distributed Systems, Software Engineering, data lifecycle, configuration platforms, low-code scripting, localisation systems, Reliability, extensibility platforms, SCALE, internationalisation, CCPA, developer productivity, data models, feature config rollout systems, data deletion systems, policy config management, platform infrastructure
Skills:
data engineering , Machine Learning, Software Development, engineering leadership, Microservices Architecture, organizational design, Stakeholder Management, OSS Contribution
Skills:
Elk, Prometheus, Grafana, Datadog, Kubernetes, GitHub Actions, OpenTelemetry, Amazon EKS, Observability systems, CI CD platforms
Skills:
Performance Engineering, Apis, Distributed Systems, Azure, AWS, Microservices, Non-Functional Quality Engineering, Cloud platforms, APM ecosystems, Observability
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