Intermediate Backend Engineer, India (Rust)

About the role

As a Staff Backend Engineer, you will provide technical leadership across your team and adjacent teams, solving the highest-scope and most complex problems in your area. You will lead large, cross-cutting backend initiatives, drive our modular architecture strategy, and define the standards that let teams move faster without compromising quality, security, reliability, or operability.

This is a technical leadership role that combines deep backend expertise, systems judgment, product judgment, and influence across organizational boundaries. You will work with Product, Frontend, Infrastructure, Security, Data, Engineering Managers, and engineers across product groups, bringing subject matter expertise, and you will do it without relying on formal authority.

Why you’ll love this role

• Leverage: Your work multiplies across teams. The platforms, standards, and architectural decisions you lead determine how quickly everyone else can ship.
• Genuinely Hard Problems: You’ll lead the modernization of a large monolith toward modular, reusable, appropriately independent systems — at the scale of a platform used by millions of users.
• Influence Without Bureaucracy: You’ll shape technical direction across teams through clear written proposals and decision records, and partner with Product and Engineering leadership on platform roadmap and investment trade-offs.
• Frontier AI Work: You’ll lead adoption of AI-assisted and agentic engineering workflows and define the review, quality, security, and privacy guardrails that make them safe to rely on.
• Autonomy: You’ll thrive in our remote-first, asynchronous organization, where clear written communication and self-direction are the pillars of success.

What you’ll do

• Lead Cross-Cutting Initiatives: Lead the technical design and delivery of large backend initiatives that span teams, and identify and remove systemic bottlenecks across product and infrastructure groups.
• Own Architecture Strategy: Drive modular backend, service, data, and platform architecture. Lead modernization of the monolith and legacy backends toward modular, reusable, and appropriately independently operated systems — while preventing fragmentation and service sprawl.
• Set the Standards: Define and improve standards for APIs, contracts, compatibility, schema evolution, testing, security, performance, observability, operability, and maintainability — plus the build, test, deploy, release, rollback, and production-readiness practices needed to operate modular features safely.
• Establish Shared Patterns: Create the patterns for dependency management, data ownership, eventing, failure isolation, service maturity, and operational documentation. Establish Go service patterns and Kubernetes operating practices where they matter to our production estate, and guide Rust adoption where it solves a real systems, security, performance, or supply-chain problem.
• Own What You Build in Production: Take part in on-call and incident response for the systems your teams own, act as a technical escalation point during complex incidents, and turn what you learn into architectural and operational improvements that prevent recurrence.
• Influence and Partner: Shape technical direction across teams without formal authority, and partner with Product and Engineering leadership on platform-level roadmap decisions and investment trade-offs.
• Grow Engineers: Mentor Senior and Intermediate engineers, shepherd technical debt reduction and reusable patterns that improve throughput, and raise the technical capability of the wider team.
• Lead AI Adoption: Lead team-level adoption of AI-assisted and agentic workflows, including the quality, security, privacy, and operational guardrails, and help engineers direct, validate, reject, and course-correct agent output.

What you’ll bring

• Cross-Team Technical Leadership: A sustained record of technical leadership across more than one team or a broad product area.
• Deep Architecture Experience: Deep backend architecture and production experience in complex applications, services, or platforms, including scaling or governing APIs, service platforms, data systems, modular monoliths, or shared backend components.
• Modularization in Production: Experience modernizing a monolith or legacy backend architecture in production, and with modular architecture such as bounded contexts, package encapsulation, ports and adapters, service extraction, event-driven boundaries, or an equivalent approach.
• Influence Without Authority: A strong ability to create alignment through clear written proposals and decision records, so decisions are documented, understood, and adopted without constant escalation.
• Product Judgment: The ability to balance customer outcomes, delivery speed, technical health, reliability, and long-term platform investment.
• Mentorship: Experience mentoring engineers and shaping standards through code review, documentation, and example.
• Agentic AI Leadership: Production experience with AI-assisted or agentic engineering workflows, including the ability to evaluate and improve how a team adopts them.

Helpful experience 

• Go services and APIs at scale.
• Kubernetes and cloud-native operations, including deployment, scaling, observability, rollback, and production readiness.
• Rust adoption or production ownership for systems, security, performance, or platform components.
• Ruby/Rails modularization and large-monolith modernization.
• PostgreSQL scaling, data partitioning, queues, messaging, or distributed systems.
• Security-sensitive product or software supply chain engineering.
• Experience across SaaS, single-tenant, self-managed, or air-gapped deployment constraints.

An overview of this role

The Trusted Agentic Development team sits within GitLab's Developer Experience group and builds the platforms our engineers rely on every day. GitLab engineers increasingly build software with artificial intelligence agents. Agents can generate code and tests in seconds, but they can also produce passing test suites for software that doesn't work as intended. As a Senior Backend Engineer, Trusted Agentic Development, you'll own the technical thesis for closing that validation gap and build the early proof yourself. You'll rethink what validation means when the author is an agent and make the feedback loop fast, automatic, and trustworthy enough that teams choose to adopt it.

• Validation that confirms agent-generated code does what was intended, so a passing suite means a working feature and not just a satisfied proxy.
• Mid-loop feedback that helps an agent self-correct toward working software instead of green assertions.
• Language-aware approaches under one shared model of what "trusted" means, starting with Rust, Ruby, and Go, while allowing the right technique to differ by language.
• Real measurement of whether engineers trust and adopt the path, fed straight back into the platform.

What you’ll do

• Own the technical thesis for how GitLab validates software when an agent is the author, and turn it into an architecture the team can build against.
• Prototype the hard parts by building early versions of feedback mechanisms that catch the gap between passing tests and working software, proving what works before the team scales it.
• Develop approaches for GitLab's primary stacks, starting with Rust, Ruby, and Go, under one shared definition of "trusted," while allowing the right technique to differ by language.
• Design the mid-loop feedback an agent needs to self-correct toward working software rather than green assertions, and build the systems that deliver it.
• Collaborate with engineering teams to adopt these approaches, measure adoption, engineer trust, and validation quality, and use those findings to improve the platform.
• Set technical direction the team can build on, review designs, and help teammates grow their technical judgment.

What you’ll bring

• Deep, current, hands-on experience building real software with artificial intelligence agents, ideally across more than one language, and a clear understanding of why agent output can pass tests yet fail in production.
• A strong point of view on the validation gap and concrete ideas for closing it, backed by approaches you've built or tried.
• Experience designing distributed systems designed to run on Kubernetes first.
• The technical range to design systems rather than tune a single framework, and the judgment to know when a solution should be general or language-specific.
• You prototype to learn, and you ship.
• The ability to influence engineers across an organization without formal authority through working code and sound reasoning.
• Strong written communication in an all-remote, asynchronous environment.
• Alignment with GitLab's values, especially collaboration, iteration, and transparency.

This isn't a quality assurance or test automation role. We aren't looking for depth in a particular testing framework. We're looking for someone who has built with agents, experienced the validation gap firsthand, and wants to solve it.

About the team

The Trusted Agentic Development team is part of GitLab's Developer Experience group. We build platforms and practices that help GitLab engineers validate agent-generated software with confidence. We work across engineering teams and programming languages to understand how people use agents, test new approaches in real workflows, and create a shared model of trusted agentic development that teams choose to adopt.

Poland base salary range: 272,000 PLN – 408,000 PLN
The base salary range for this role’s listed level is currently for residents of the EU, applicable in the specified country or countries only. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location and having regard to any applicable collective agreements. The base salary range does not include bonuses, equity, or benefits.

 

The Product

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.

We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.

The Role

We are looking for a Senior Software Engineer to work on the indexing and data processing layer of a novel search engine tailored for agentic AI consumption.

In this role, you will focus on building systems that ingest, process, and organise massive volumes of data into efficient, queryable structures. You will work primarily on offline and nearline pipelines, ensuring that data is fresh, complete, and efficiently accessible by downstream retrieval systems. You will operate in an environment where throughput, scalability, and correctness are critical; designing systems capable of handling tens of gigabytes per second across continuously evolving datasets.

In this position, your responsibility will be to:

• Design, implement, and operate large-scale indexing systems and data pipelines that sit at the core of our search infrastructure
• Develop and optimise indexing strategies balancing performance, freshness, and resource efficiency
• Work on storage formats, compaction strategies, and update mechanisms to keep data accessible and current
• Ensure reliability and predictability of pipelines under high-throughput conditions
• Build well-tested components with clear responsibilities and interaction contracts, while remaining flexible as the system evolves
• Define and implement observability primitives, including structured logs, metrics, and data quality signals across offline and nearline pipelines
• Monitor throughput, resource usage, and cost, and drive optimisations when business needs require it
• Collaborate with runtime and ML teams to ensure indexing outputs meet retrieval and ranking requirements
• Enable safe experimentation on indexing strategies and data processing logic through controlled rollouts and clearly defined quality signals

You may be a good fit if you:

• 5+ years of experience building production backend or data infrastructure systems
• Strong Go experience (C++/Rust is a plus)
• Experience with large-scale data processing systems (10+ GiB/sec throughput, petabyte-scale datasets, etc.)
• Experience building or operating databases, storage systems, data planes, or indexing pipelines
• Strong understanding of distributed systems, fault tolerance, consistency, and scalability
• Experience running production systems and handling operational incidents
• Systems-thinking mindset and ability to reason about end-to-end data flows

Strong candidates may also have experience with:

• Distributed data processing frameworks such as Spark, Flink, MapReduce, or Beam
• Content systems including, scraping, proxying, or anti-bot infrastructure
• Ad tech, social networks, or other large-scale content platforms
• DBMS internals (open source or SaaS) and cloud infrastructure
• Open-source contributions or active involvement in the engineering community
• Competitive programming or CTF participation (ICPC, IOI, or similar)
• SHAD or similar advanced technical programmes
• Conference talks or technical publications

 

We conduct coding interviews as part of the process.