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Senior Software Engineer

Perceptive

Full time
Location
India
Work mode
Not stated
Salary
₹11L – ₹25L a year estimatetypical for IT Jobs in India, 825 posts
Posted 11 days ago

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Role at a glance

You will
  • As Senior Software Engineer, Medical Imaging you will contribute to the design and development of scalable, secure, and compliant…
  • You will provide designs and solutions for cloud-native solutions, DICOM image workflows, AI/ML integrations, and regulatory compliance…
  • Supporting Activities
Must-have skills
GraphQL API DevelopmentJavaMLOpsREST API DevelopmentEncryption

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Job description

We’re on a mission to change the future of
clinical research. At Perceptive, we help the
biopharmaceutical industry bring medical
treatments to the market, faster.
Our mission is to change the world
but to do this, we need people like you.

Apart from job satisfaction, we can offer you:

HEALTH:

- Medical plan for you and your dependents.

- Personal Accident Insurance

- Life Insurance

- Critical illness cover

WEALTH:

- Salary structure and Flexi basket

- Provident fund of 12%

- Gratuity scheme

YOURSELF: Internal growth and development programs & trainings

Job Summary:

As Senior Software Engineer, Medical Imaging you will contribute to the design and development of scalable, secure, and compliant cloud-native solutions that transform medical imaging workflows in clinical trials. You will provide designs and solutions for cloud-native solutions, DICOM image workflows, AI/ML integrations, and regulatory compliance while contributing to innovation in medical imaging technology.

Key Responsibilities:

Supporting Activities

Cloud-Native SaaS Architecture Design

  • Implement scalable, multi-tenant SaaS components using cloud-native services.
  • Design and develop microservices for medical imaging data processing and AI workloads.
  • Implement auto-scaling and load balancing features for medical imaging datasets.
  • Develop API endpoints and service integrations with clinical trial systems.
  • Support platform scalability for concurrent clinical trials and imaging workflows.

AI-Driven Medical Imaging Platform Development

  • Implement AI/ML model integrations for medical image analysis, including genAI, computer vision and deep learning algorithms.
  • Develop systems for real-time and batch processing of medical imaging data (DICOM, NIfTI, etc.).
  • Implement DICOM-compliant data processing pipelines.
  • Develop efficient DICOM image preprocessing workflows for AI model preparation.
  • Support AI model deployment and monitoring in production environments.

Medical Image Viewer Integration & Workflow Design

  • Develop integration components for third-party medical imaging viewers (OHIF, Cornerstone.js, or proprietary systems).
  • Implement APIs and SDK components for clinical trial management system integration.
  • Develop collaboration features for multi-site clinical trials.
  • Create visualization components for AI-generated insights and annotations.
  • Ensure responsive design implementation for various devices and browsers.

Security & Compliance Implementation

  • Implement security features compliant with FDA 21 CFR Part 11, GxP, and medical device regulations.
  • Develop audit trails, electronic signatures, and data integrity controls.
  • Implement encryption, role-based access control, and authentication features.
  • Support disaster recovery and backup solutions for clinical trial data.

Database & Data Management

  • Implement high-performance database solutions for DICOM metadata storage and retrieval and AI model outputs.
  • Develop solutions for the storage, analysis, access, and movement of large-scale medical imaging datasets.
  • Implement data processing pipelines for large-scale DICOM datasets.
  • Develop real-time data streaming components for live DICOM image analysis.
  • Implement data governance features ensuring data quality and privacy protection.

Performance Optimization & Monitoring

  • Implement monitoring and observability components for SaaS platform performance.
  • Optimize system performance for medical imaging file processing and transfer.
  • Implement caching strategies and CDN integration for global access.
  • Develop automated alerting and performance monitoring features.
  • Support SLA compliance and platform reliability initiatives.

Technical Development & Support

  • Contribute to technology stack decisions for medical imaging and AI workloads.
  • Support adoption of emerging technologies in medical imaging and AI/ML.
  • Participate in code reviews and maintain development best practices.
  • Support coding standards, development processes, and quality assurance.
  • Collaborate in technical architecture reviews and system design decisions.

Innovation

  • Take an active interest in emerging technologies in medical imaging, AI/ML, and cloud computing.
  • Monitor the market to gather intelligence on emerging technologies.
  • Share knowledge and insights with others.

Other

  • Carryout any other reasonable duties as requested.

Functional Competencies (Technical knowledge/Skills):

  • Knowledge of containerization and serverless architectures
  • Knowledge of message queuing systems for high-throughput medical data processing
  • Knowledge of DICOM networking protocols (DICOM C-STORE, C-FIND, C-MOVE) and DICOMweb services
  • Knowledge of security frameworks, encryption, and identity management solutions
  • Understanding of medical imaging modalities (CT, MRI, X-Ray, PET, Ultrasound) and clinical workflows
  • Knowledge of clinical trial processes, regulatory requirements, and quality management systems
  • Familiarity with AI applications in medical imaging (computer-aided diagnosis, image segmentation, etc.)
  • Good technical communication skills with ability to work effectively in cross-functional teams
  • Ability to communicate technical concepts to clinical and business stakeholders
  • Ability to balance technical requirements with business objectives
  • Understanding of DICOM standard implementation, including DICOM conformance statements and IHE integration profiles
  • Understanding of medical imaging modalities (CT, MRI, X-Ray, PET, Ultrasound) and their specific DICOM implementations
  • Knowledge of clinical trial processes, regulatory requirements, and quality management systems
  • Familiarity with AI applications in medical imaging using DICOM datasets

Behavior Competencies:

  • Accountability
  • Adaptability
  • Customer focus
  • Robust
  • Decision Making
  • Business Acumen
  • Results orientation
  • Time Management
  • Willingness to learn
  • Team collaboration

Experience, Education and Certifications

  • Substantial post-qualification software development experience, with a strong track record of delivering solutions in medical imaging or healthcare technology
  • Experience developing cloud-native applications and SaaS components
  • Experience with AI/ML integration in production environments, preferably in medical imaging
  • Experience with regulated software development (FDA, GxP, ISO 13485) processes
  • Background in medical imaging file formats, processing libraries, and viewer integrations
  • Experience with clinical trial management systems or electronic data capture (EDC) platform.
  • Solid expertise in cloud platforms with a strong understanding of serverless and scalable architectures, modern cloud-native services, and integration with AI/ML services
  • Proficiency in developing RESTful APIs, GraphQL, and real-time communication protocols
  • Experience with medical imaging standards (DICOM, HL7 FHIR) and DICOM processing libraries (pydicom, DCMTK, GDCM)
  • Experience with DICOM standard implementation, including DICOM parsing libraries and tag manipulation
  • Exposure to AI/ML solutions within imaging platforms, as well as MLOps practices
  • Experience in database design for both relational and NoSQL systems
  • Experience with medical image viewer technologies and PACS integration
  • Experience working in regulated environments
  • Experience with DICOM image processing workflows, anonymization techniques, and metadata preservation
  • Experience with medical image viewer technologies, PACS integration, and DICOM routing workflows
  • Proficiency in Java, J2EE

Come as you are.

We're proud to be a Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Key skills

Required

GraphQL API DevelopmentJavaMLOpsREST API DevelopmentEncryption

Job market insights

222active GraphQL API Development jobs in India
2,290active Java jobs in India
315active MLOps jobs in India
₹11L – ₹25L advertised yearly salary for IT Jobs in India (middle half of 825 posts that show a salary; median ₹17L)
1 more open job at Perceptive

Jobs asking for GraphQL API Development in India also ask for

  • AWS57%
  • CI/CD55%
  • React50%
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  • Java45%

From live job posts on CoreHRx, updated 12 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.

Questions about this job

What is the salary for this Senior Software Engineer job?

The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹11L – ₹25L a year (typical for IT Jobs in India, 825 posts).

What kind of job is this?

It is a full time job.

This guide is for Indian job seekers preparing for Java backend roles, from freshers facing campus and first-job interviews to experienced developers moving into senior positions at product companies and IT services firms. It covers what interviewers ask most in 2025 and 2026 on Java 17 and 21 and Spring Boot 3: OOP, collections, equals and hashCode, streams, exceptions, concurrency and JVM memory, then dependency injection, auto-configuration, REST controllers, validation, JPA and Hibernate, security, microservices and testing. Questions are grouped as easy, medium and hard. Read each answer, compile the code yourself and practise explaining it aloud.

Questions you may be asked

  1. What are the four pillars of OOP, with a Java example of each?
  2. What is the difference between an abstract class and an interface in Java?
  3. What is the difference between method overloading and method overriding?
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