Specialist Software Engineer
Amgen
Specialist Software Engineer
Job Description
ABOUT AMGEN
What you will do
- Design, develop, and maintain software applications and solutions that meet business needs
- Ensure the availability and performance of critical systems and applications
- Work closely with product managers, designers, and other engineers to create high-quality, scalable software solutions
- Automate operations, monitor system health, and respond to incidents to minimize downtime
- Own end-to-end architecture and implementation for high-impact services and platforms (APIs, data pipelines, microservices, event-driven systems)
- Write clean, well-tested code; perform design and code reviews; establish quality gates and engineering standards
- Drive cloud-native designs (AWS/Azure/GCP), container orchestration (Kubernetes), and Infrastructure as Code (Terraform/CloudFormation/Bicep)
- Build and operate CI/CD pipelines and automated testing (unit, integration, contract, performance, security)
- Champion reliability (observability, SLOs/SLIs, incident response, postmortems) and performance tuning at scale
- Ensure security by design (threat modeling, least privilege, secrets management, vulnerability remediation, secure SDLC)
- Partner with product, data, and security to align architecture with business outcomes and compliance needs
- Lead technical discovery, RFCs, and POCs; make build/buy decisions and guide vendor integrations
- Mentor engineers across teams; provide technical guidance, pairing, and knowledge-sharing
- Create clear documentation, runbooks, and architectural diagrams; drive operational readiness
- Provide technical guidance and mentorship to junior developers
- Contribute to both front-end and back-end development using cloud technology
- Develop innovative solutions using generative AI technologies
- Conduct code reviews to ensure code quality and adherence to best practices
- Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
- Stay updated with the latest trends and advancements
- Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
- Identify and resolve software bugs and performance issues
- Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software on time
- Integrate systems and platforms to ensure seamless data flow and functionality
- Collaborate with data scientists to develop, train, and evaluate machine learning models
- Build and maintain MLOps pipelines leveraging cloud platform, including data ingestion, feature engineering, model training, deployment, and monitoring
- Deploy machine learning models into production environments, ensuring that they are scalable and maintainable
- Design and implement systems and processes to improve the reliability, scalability, and performance of applications
- Automate routine operational tasks, such as deployments, monitoring, and incident response, to improve efficiency and reduce human error
- Develop and maintain monitoring tools and dashboards to track system health, performance, and availability
What we expect of you
- Master’s degree with 6 - 8 years of experience in Computer Science, IT or related field OR Bachelor’s degree with 8 - 12 years of experience in Computer Science, IT or related field
Must-Have Skills
- Solid foundation in modern software design and engineering practices, with a specific focus incorporating AI and ML into solutions, including low code, microservice, serverless cloud, and containerization platforms
- Strong experience on Agile software development teams
- Strong proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and MLOps (e.g., MLflow, Kubeflow, Airflow)
- Hands on experience with Full Stack software development. Proficient in programming language Python (preferred), JavaScript, SQL/NoSQL
- Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)
- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)
- Experience with data processing tools like Hadoop, Spark, or similar
- Excellent analytical and troubleshooting skills
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation
- Ability to manage multiple priorities successfully
- Team-oriented, with a focus on achieving team goals
- Strong presentation and public speaking skills
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
30,000 - 60,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Solid foundation in modern software design and engineering practices, with a specific focus incorporating AI and ML into solutions, including low code, microservice, serverless cloud, and containerization platformsintermediate
- Strong experience on Agile software development teamsintermediate
- Strong proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and MLOps (e.g., MLflow, Kubeflow, Airflow)intermediate
- Hands on experience with Full Stack software development. Proficient in programming language Python (preferred), JavaScript, SQL/NoSQLintermediate
- Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)intermediate
- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)intermediate
- Experience with data processing tools like Hadoop, Spark, or similarintermediate
- Excellent analytical and troubleshooting skillsintermediate
- Strong verbal and written communication skillsintermediate
- Ability to work effectively with global, virtual teamsintermediate
- High degree of initiative and self-motivationintermediate
- Ability to manage multiple priorities successfullyintermediate
- Team-oriented, with a focus on achieving team goalsintermediate
- Strong presentation and public speaking skillsintermediate
Required Qualifications
- Master’s degree with 6 - 8 years of experience in Computer Science, IT or related field OR Bachelor’s degree with 8 - 12 years of experience in Computer Science, IT or related field (experience)
Responsibilities
- Design, develop, and maintain software applications and solutions that meet business needs
- Ensure the availability and performance of critical systems and applications
- Work closely with product managers, designers, and other engineers to create high-quality, scalable software solutions
- Automate operations, monitor system health, and respond to incidents to minimize downtime
- Own end-to-end architecture and implementation for high-impact services and platforms (APIs, data pipelines, microservices, event-driven systems)
- Write clean, well-tested code; perform design and code reviews; establish quality gates and engineering standards
- Drive cloud-native designs (AWS/Azure/GCP), container orchestration (Kubernetes), and Infrastructure as Code (Terraform/CloudFormation/Bicep)
- Build and operate CI/CD pipelines and automated testing (unit, integration, contract, performance, security)
- Champion reliability (observability, SLOs/SLIs, incident response, postmortems) and performance tuning at scale
- Ensure security by design (threat modeling, least privilege, secrets management, vulnerability remediation, secure SDLC)
- Partner with product, data, and security to align architecture with business outcomes and compliance needs
- Lead technical discovery, RFCs, and POCs; make build/buy decisions and guide vendor integrations
- Mentor engineers across teams; provide technical guidance, pairing, and knowledge-sharing
- Create clear documentation, runbooks, and architectural diagrams; drive operational readiness
- Provide technical guidance and mentorship to junior developers
- Contribute to both front-end and back-end development using cloud technology
- Develop innovative solutions using generative AI technologies
- Conduct code reviews to ensure code quality and adherence to best practices
- Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
- Stay updated with the latest trends and advancements
- Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
- Identify and resolve software bugs and performance issues
- Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software on time
- Integrate systems and platforms to ensure seamless data flow and functionality
- Collaborate with data scientists to develop, train, and evaluate machine learning models
- Build and maintain MLOps pipelines leveraging cloud platform, including data ingestion, feature engineering, model training, deployment, and monitoring
- Deploy machine learning models into production environments, ensuring that they are scalable and maintainable
- Design and implement systems and processes to improve the reliability, scalability, and performance of applications
- Automate routine operational tasks, such as deployments, monitoring, and incident response, to improve efficiency and reduce human error
- Develop and maintain monitoring tools and dashboards to track system health, performance, and availability
Tags & Categories
Specialist Software Engineer
Amgen
Specialist Software Engineer
Job Description
ABOUT AMGEN
What you will do
- Design, develop, and maintain software applications and solutions that meet business needs
- Ensure the availability and performance of critical systems and applications
- Work closely with product managers, designers, and other engineers to create high-quality, scalable software solutions
- Automate operations, monitor system health, and respond to incidents to minimize downtime
- Own end-to-end architecture and implementation for high-impact services and platforms (APIs, data pipelines, microservices, event-driven systems)
- Write clean, well-tested code; perform design and code reviews; establish quality gates and engineering standards
- Drive cloud-native designs (AWS/Azure/GCP), container orchestration (Kubernetes), and Infrastructure as Code (Terraform/CloudFormation/Bicep)
- Build and operate CI/CD pipelines and automated testing (unit, integration, contract, performance, security)
- Champion reliability (observability, SLOs/SLIs, incident response, postmortems) and performance tuning at scale
- Ensure security by design (threat modeling, least privilege, secrets management, vulnerability remediation, secure SDLC)
- Partner with product, data, and security to align architecture with business outcomes and compliance needs
- Lead technical discovery, RFCs, and POCs; make build/buy decisions and guide vendor integrations
- Mentor engineers across teams; provide technical guidance, pairing, and knowledge-sharing
- Create clear documentation, runbooks, and architectural diagrams; drive operational readiness
- Provide technical guidance and mentorship to junior developers
- Contribute to both front-end and back-end development using cloud technology
- Develop innovative solutions using generative AI technologies
- Conduct code reviews to ensure code quality and adherence to best practices
- Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
- Stay updated with the latest trends and advancements
- Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
- Identify and resolve software bugs and performance issues
- Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software on time
- Integrate systems and platforms to ensure seamless data flow and functionality
- Collaborate with data scientists to develop, train, and evaluate machine learning models
- Build and maintain MLOps pipelines leveraging cloud platform, including data ingestion, feature engineering, model training, deployment, and monitoring
- Deploy machine learning models into production environments, ensuring that they are scalable and maintainable
- Design and implement systems and processes to improve the reliability, scalability, and performance of applications
- Automate routine operational tasks, such as deployments, monitoring, and incident response, to improve efficiency and reduce human error
- Develop and maintain monitoring tools and dashboards to track system health, performance, and availability
What we expect of you
- Master’s degree with 6 - 8 years of experience in Computer Science, IT or related field OR Bachelor’s degree with 8 - 12 years of experience in Computer Science, IT or related field
Must-Have Skills
- Solid foundation in modern software design and engineering practices, with a specific focus incorporating AI and ML into solutions, including low code, microservice, serverless cloud, and containerization platforms
- Strong experience on Agile software development teams
- Strong proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and MLOps (e.g., MLflow, Kubeflow, Airflow)
- Hands on experience with Full Stack software development. Proficient in programming language Python (preferred), JavaScript, SQL/NoSQL
- Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)
- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)
- Experience with data processing tools like Hadoop, Spark, or similar
- Excellent analytical and troubleshooting skills
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation
- Ability to manage multiple priorities successfully
- Team-oriented, with a focus on achieving team goals
- Strong presentation and public speaking skills
Locations
- Hyderabad, India
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
30,000 - 60,000 USD / yearly
Source: xAI estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Solid foundation in modern software design and engineering practices, with a specific focus incorporating AI and ML into solutions, including low code, microservice, serverless cloud, and containerization platformsintermediate
- Strong experience on Agile software development teamsintermediate
- Strong proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and MLOps (e.g., MLflow, Kubeflow, Airflow)intermediate
- Hands on experience with Full Stack software development. Proficient in programming language Python (preferred), JavaScript, SQL/NoSQLintermediate
- Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)intermediate
- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)intermediate
- Experience with data processing tools like Hadoop, Spark, or similarintermediate
- Excellent analytical and troubleshooting skillsintermediate
- Strong verbal and written communication skillsintermediate
- Ability to work effectively with global, virtual teamsintermediate
- High degree of initiative and self-motivationintermediate
- Ability to manage multiple priorities successfullyintermediate
- Team-oriented, with a focus on achieving team goalsintermediate
- Strong presentation and public speaking skillsintermediate
Required Qualifications
- Master’s degree with 6 - 8 years of experience in Computer Science, IT or related field OR Bachelor’s degree with 8 - 12 years of experience in Computer Science, IT or related field (experience)
Responsibilities
- Design, develop, and maintain software applications and solutions that meet business needs
- Ensure the availability and performance of critical systems and applications
- Work closely with product managers, designers, and other engineers to create high-quality, scalable software solutions
- Automate operations, monitor system health, and respond to incidents to minimize downtime
- Own end-to-end architecture and implementation for high-impact services and platforms (APIs, data pipelines, microservices, event-driven systems)
- Write clean, well-tested code; perform design and code reviews; establish quality gates and engineering standards
- Drive cloud-native designs (AWS/Azure/GCP), container orchestration (Kubernetes), and Infrastructure as Code (Terraform/CloudFormation/Bicep)
- Build and operate CI/CD pipelines and automated testing (unit, integration, contract, performance, security)
- Champion reliability (observability, SLOs/SLIs, incident response, postmortems) and performance tuning at scale
- Ensure security by design (threat modeling, least privilege, secrets management, vulnerability remediation, secure SDLC)
- Partner with product, data, and security to align architecture with business outcomes and compliance needs
- Lead technical discovery, RFCs, and POCs; make build/buy decisions and guide vendor integrations
- Mentor engineers across teams; provide technical guidance, pairing, and knowledge-sharing
- Create clear documentation, runbooks, and architectural diagrams; drive operational readiness
- Provide technical guidance and mentorship to junior developers
- Contribute to both front-end and back-end development using cloud technology
- Develop innovative solutions using generative AI technologies
- Conduct code reviews to ensure code quality and adherence to best practices
- Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
- Stay updated with the latest trends and advancements
- Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
- Identify and resolve software bugs and performance issues
- Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software on time
- Integrate systems and platforms to ensure seamless data flow and functionality
- Collaborate with data scientists to develop, train, and evaluate machine learning models
- Build and maintain MLOps pipelines leveraging cloud platform, including data ingestion, feature engineering, model training, deployment, and monitoring
- Deploy machine learning models into production environments, ensuring that they are scalable and maintainable
- Design and implement systems and processes to improve the reliability, scalability, and performance of applications
- Automate routine operational tasks, such as deployments, monitoring, and incident response, to improve efficiency and reduce human error
- Develop and maintain monitoring tools and dashboards to track system health, performance, and availability
Tags & Categories