LinkedIn

Internet

SeniorSoftwareEngineer-ProductivityEngineering

₹25–45L ~AI est. Bengaluru, Karnataka, India FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior Software Engineer - Productivity Engineering at LinkedIn. Skills: AI agent systems, LLM integration, System design, Production operations. Investigate employee productivity pain points. Synthesize signals from data”

What You'll Achieve.

Raise technical bar; Replace manual support experiences; Put AI at center; Build, evaluate, operate systems at scale; Ship systems; Own problem space; Translate ambiguous signals; Build with rigor; Ensure systems are debuggable; Ensure systems are auditable; Ensure systems are continuously improvable; Balance expressiveness with guardrails; Raise floor for IC2s

Industry & Context.

Internet
Problems you'll solve

Strategic problem solving; Troubleshooting

What They're Looking For.

Must Have

Bachelor's degree in Computer Science or related technical field, or equivalent practical experience, 5–8 years of software engineering experience, Deep expertise in Python/Java, Proficiency in FastAPI / Asyncio, Pydantic, and high-concurrency event loops, Proficiency in Spring Boot / Quarkus, Reactive programming, and JVM performance tuning, Proven experience designing and implementing high-performance REST and gRPC APIs, Understanding of distributed system patterns, Track record of owning and delivering complex systems end-to-end, SRE mindset, Demonstrated ability to independently identify and frame engineering problems, Hands-on experience integrating LLM APIs

Nice to Have

Experience designing or leading AI agent systems, Command of AI-native SDLC practices, Experience with workflow orchestration and durable execution frameworks, Track record of establishing engineering standards, Experience integrating deeply with enterprise SaaS platforms

What You'll Do.

Investigate employee productivity pain points

Synthesize signals from data

Derive solution context

Translate problem contexts into technical designs

Make principled tradeoffs

Architect AI agentic systems

Deliver Python-based services

Orchestrate LLM-powered agents

Define AI-native engineering approach

Define eval-driven development

Define agent observability

Define prompt lifecycle management

Define safe autonomous action

Own standards for testing

Own standards for tracing

Own standards for monitoring

Design tool ecosystem for agents

Interact with internal platforms

Provide technical guidance

Conduct design reviews

Mentor IC2s on AI systems

Partner with product teams

Partner with operations teams

Partner with platform teams

Identify automation opportunities

Shape engineering roadmap

How You'll Work.

Team & Collaboration

Cross-functional roadmap; Partner with product; Partner with operations; Partner with platform

Communication Scope

Technical direction; Measurable outcomes

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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