Staff Software Engineer - Full Stack
Software Engineering
Bengaluru, Karnataka, India
Posted on May 1, 2025
LinkedIn was built to help professionals achieve more in their careers, and everyday millions of people use our products to make connections, discover opportunities and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We are much more than a digital resume – we transform lives through innovative products and technology.
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
This role will be based in Bangalore, India
Productivity Engineering is a team at LinkedIn that builds products that power LinkedIn’s business. We drive technology vision, architecture, and design systems that help the company deliver major business processes (talent acquisitions, sales, finance, and customer support etc.). We deliver applications and products that let our customers do business with us in a seamless way, help grow our top line, and increase our efficiency.
As a part of the Talent Productivity Engineering team, you will be building out custom web solutions and integrations that LinkedIn employees don’t just use, but love. This is an innovative team working with various parties involved in the candidate and employee journeys. Our work directly impacts the way LinkedIn hires, develops, and engages the best talent across the globe.
As a Staff Software Engineer, you will lead the design and deployment of intelligent, AI-powered integration solutions across LinkedIn’s enterprise ecosystem. This role combines deep cloud engineering, modern software development, and applied AI to build systems that automate, predict, and accelerate business processes. You'll architect scalable services that harness the power of Generative AI, Agentic AI, and cloud-native frameworks to connect enterprise systems and deliver meaningful insights and automation across platform
Responsibilities:
- Architect and build intelligent integration frameworks and backend services leveraging AI models (OpenAI, custom LLMs, ML pipelines) and Azure services (APIM, Function Apps, Event Hubs, Azure SQL).
- Design and operationalize AI-first solutions that process, enrich, and serve enterprise data at scale.
- Design & Develop complex, enterprise-grade integration and AI solutions using open-source frameworks, Azure services (e.g., APIM, Function Apps, Event Hubs, Azure SQL), and AI services including OpenAI.
- Own end-to-end service lifecycle—design, development, deployment, observability, and iteration.
- Implement and expose AI capabilities through APIs and microservices that integrate with internal applications and SaaS platforms, ensuring optimal performance and seamless functionality.
- Collaborate with engineers, AI researchers, product managers, and UX designers to translate business problems into scalable AI-powered services.
- Lead technical reviews, architecture decisions, and AI integration patterns across teams.
- Stay ahead of trends in Generative AI, Agentic AI, and MLOps; continuously identify opportunities to embed intelligence into systems.
- Drive quality through test automation frameworks, CI/CD pipelines, and performance engineering.
- Document and evangelize best practices for secure, ethical, and responsible use of AI in enterprise environments.
Basic Qualifications:
- 9+ years of software engineering experience in backend or systems integration roles.
- BS in Computer Science, Engineering, or equivalent.
- Proficiency in Python (or Java) for backend development and AI integration.
- Hands-on experience designing and deploying REST APIs, event-driven architectures, and microservices using cloud platforms (Azure, AWS, GCP).
- Good experience in building production-grade frontend applications using React and JavaScript, with attention to design systems, performance, and accessibility.
- Good experience with AI technologies (e.g., OpenAI, Hugging Face, LangChain) and AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
- Prior experience in Generative AI and Agentic AI.
- Skilled in relational and non-relational data systems (PostgreSQL, - - - - MySQL, Azure SQL, NoSQL), ETL pipelines, and data modeling.
- Experience with test frameworks (e.g., Pytest), version control (Git), CI/CD (Jenkins), and containerization (Docker, Kubernetes).
Preferred Qualifications:
- Highly self-driven, execution-focused, with a willingness to do “what it takes” to deliver results as you will be expected to rapidly cover a considerable amount of ground.
- Prior experience integrating AI into enterprise workflows—e.g., chatbots, intelligent agents, AI-enhanced APIs.
- Familiarity with MLOps tools and infrastructure-as-code (Terraform, Ansible).
- Experience with Workday, SAP, or other ERP/HR systems.
- Workday integration experience a plus
- Exposure to edge computing, IoT, or real-time AI decision engines.
- Track record of mentoring teams, driving engineering culture, and influencing strategic architecture decisions.
- Good written and verbal communication, with a passion for innovation and continuous learning.
- Challenges the status quo, fosters an innovative culture, and continuously learns new digital tools and methodologies
Suggested Skill:
• Python, Java, REST APIs, Web Services, Django/Flask/FastAPI
• OpenAI, LangChain, Hugging Face, TensorFlow, PyTorch, Scikit-Learn, Responsible AI principles
• Azure (APIM, Functions, Event Hubs), AWS, GCP, Docker, Kubernetes, Terraform, Jenkins, Git
• SQL/NoSQL, ETL Pipelines, Azure SQL, PostgreSQL, MySQL
• JavaScript, React
• Microservices, Event-Driven Systems, MLOps, CI/CD, Observability
India Disability Policy
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
Global Data Privacy Notice for Job Candidates
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
This role will be based in Bangalore, India
Productivity Engineering is a team at LinkedIn that builds products that power LinkedIn’s business. We drive technology vision, architecture, and design systems that help the company deliver major business processes (talent acquisitions, sales, finance, and customer support etc.). We deliver applications and products that let our customers do business with us in a seamless way, help grow our top line, and increase our efficiency.
As a part of the Talent Productivity Engineering team, you will be building out custom web solutions and integrations that LinkedIn employees don’t just use, but love. This is an innovative team working with various parties involved in the candidate and employee journeys. Our work directly impacts the way LinkedIn hires, develops, and engages the best talent across the globe.
As a Staff Software Engineer, you will lead the design and deployment of intelligent, AI-powered integration solutions across LinkedIn’s enterprise ecosystem. This role combines deep cloud engineering, modern software development, and applied AI to build systems that automate, predict, and accelerate business processes. You'll architect scalable services that harness the power of Generative AI, Agentic AI, and cloud-native frameworks to connect enterprise systems and deliver meaningful insights and automation across platform
Responsibilities:
- Architect and build intelligent integration frameworks and backend services leveraging AI models (OpenAI, custom LLMs, ML pipelines) and Azure services (APIM, Function Apps, Event Hubs, Azure SQL).
- Design and operationalize AI-first solutions that process, enrich, and serve enterprise data at scale.
- Design & Develop complex, enterprise-grade integration and AI solutions using open-source frameworks, Azure services (e.g., APIM, Function Apps, Event Hubs, Azure SQL), and AI services including OpenAI.
- Own end-to-end service lifecycle—design, development, deployment, observability, and iteration.
- Implement and expose AI capabilities through APIs and microservices that integrate with internal applications and SaaS platforms, ensuring optimal performance and seamless functionality.
- Collaborate with engineers, AI researchers, product managers, and UX designers to translate business problems into scalable AI-powered services.
- Lead technical reviews, architecture decisions, and AI integration patterns across teams.
- Stay ahead of trends in Generative AI, Agentic AI, and MLOps; continuously identify opportunities to embed intelligence into systems.
- Drive quality through test automation frameworks, CI/CD pipelines, and performance engineering.
- Document and evangelize best practices for secure, ethical, and responsible use of AI in enterprise environments.
Basic Qualifications:
- 9+ years of software engineering experience in backend or systems integration roles.
- BS in Computer Science, Engineering, or equivalent.
- Proficiency in Python (or Java) for backend development and AI integration.
- Hands-on experience designing and deploying REST APIs, event-driven architectures, and microservices using cloud platforms (Azure, AWS, GCP).
- Good experience in building production-grade frontend applications using React and JavaScript, with attention to design systems, performance, and accessibility.
- Good experience with AI technologies (e.g., OpenAI, Hugging Face, LangChain) and AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
- Prior experience in Generative AI and Agentic AI.
- Skilled in relational and non-relational data systems (PostgreSQL, - - - - MySQL, Azure SQL, NoSQL), ETL pipelines, and data modeling.
- Experience with test frameworks (e.g., Pytest), version control (Git), CI/CD (Jenkins), and containerization (Docker, Kubernetes).
Preferred Qualifications:
- Highly self-driven, execution-focused, with a willingness to do “what it takes” to deliver results as you will be expected to rapidly cover a considerable amount of ground.
- Prior experience integrating AI into enterprise workflows—e.g., chatbots, intelligent agents, AI-enhanced APIs.
- Familiarity with MLOps tools and infrastructure-as-code (Terraform, Ansible).
- Experience with Workday, SAP, or other ERP/HR systems.
- Workday integration experience a plus
- Exposure to edge computing, IoT, or real-time AI decision engines.
- Track record of mentoring teams, driving engineering culture, and influencing strategic architecture decisions.
- Good written and verbal communication, with a passion for innovation and continuous learning.
- Challenges the status quo, fosters an innovative culture, and continuously learns new digital tools and methodologies
Suggested Skill:
• Python, Java, REST APIs, Web Services, Django/Flask/FastAPI
• OpenAI, LangChain, Hugging Face, TensorFlow, PyTorch, Scikit-Learn, Responsible AI principles
• Azure (APIM, Functions, Event Hubs), AWS, GCP, Docker, Kubernetes, Terraform, Jenkins, Git
• SQL/NoSQL, ETL Pipelines, Azure SQL, PostgreSQL, MySQL
• JavaScript, React
• Microservices, Event-Driven Systems, MLOps, CI/CD, Observability
India Disability Policy
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
Global Data Privacy Notice for Job Candidates
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal