Technology
SeniorSoftwareEngineer-ProductivityEngineering
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Software Engineer - Productivity Engineering at LinkedIn. Skills: AI agentic systems, LLM integration, Productivity automation. Own problem statements end-to-end. Investigate employee productivity pain points”
What You'll Achieve.
Raise the technical bar; Measurable outcomes
Industry & Context.
Strategic Problem Solving; Troubleshooting
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, 5–8 years software engineering experience, Expertise in Python or Java, Proficiency in FastAPI / Asyncio, Proficiency in Spring Boot / Quarkus, Reactive programming experience, JVM performance tuning, High-performance REST and gRPC APIs, Distributed system patterns, Owning and delivering complex systems, Identify and frame engineering problems, Integrate LLM APIs
Nice to Have
Experience with Vector Databases, Experience with Message Queues, Experience with Relational databases, Experience with Object Storage, Understanding of RAG data modeling, Experience with enterprise SaaS platforms, Designing resilient integration layers
What You'll Do.
Own problem statements end-to-end
Investigate employee productivity pain points
Synthesize signals from data
Derive solution context
Drive solution architecture
Translate problem contexts into technical designs
Make tradeoffs across reliability
Architect and deliver AI agentic systems
Orchestrate LLM-powered agents
Set technical direction for AI-native engineering
Define eval-driven development
Define agent observability
Define prompt lifecycle management
Define safe autonomous action
Drive system reliability and quality
Own standards for testing
Expand agent capability surface
Design tool ecosystem for agents
Balance expressiveness with guardrails
Mentor and grow the team
Provide technical guidance
Raise the floor for AI systems work
Influence cross-functional roadmap
Identify automation opportunities
Shape engineering roadmap
How You'll Work.
Team & Collaboration
Cross-functional roadmap; Partner with product teams; Partner with operations teams; Partner with platform teams
Process & Methodology
Roadmap planning
Full Job Description
LinkedIn was built to help professionals achieve more in their careers, and every day 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’re 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. We are looking for a Senior Software Engineer to join the Productivity Engineering team in Bangalore, where our mission is to transform how employees work by replacing manual, fragmented support experiences with intelligent, AI-native automation. You will lead the design and delivery of end-to-end agentic systems that put AI at the center of the employee productivity loop — and raise the technical bar for how the team builds, evaluates, and operates these systems at scale. This is a high-ownership, high-scope role. Beyond shipping systems, you will own the problem space: independently investigating employee pain points, deriving solution contexts, and translating ambiguous signals into engineering initiatives with clear technical direction and measurable outcomes. You will set standards for how the team approaches AI-native development and mentor others to build with the same rigor. Responsibilities: · Own problem statements end-to-end — proactively investigate employee productivity pain points, synthesize signals from data, stakeholders, and operations, and derive the solution context that frames what we build and why. · Drive solution architecture — translate well-understood problem contexts into technical designs for agentic systems, making principle
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