Full-Time

Senior Site Reliability Engineer

Nexla

Nexla

51-200 employees

No-code data integration for AI

No salary listed

Bengaluru, Karnataka, India

In Person

Category
DevOps & Infrastructure (1)
Required Skills
Kubernetes
Python
GitHub Actions
BigQuery
Apache Spark
Apache Kafka
AWS
Jenkins
Terraform
Redis
Snowflake
Google Cloud Platform

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Requirements
  • Experience: 8+ years in infrastructure, SRE, or DevOps, with significant time spent operating production distributed data systems (not just application/cloud infra).
  • Kafka: Deep, hands-on operational experience running Kafka at scale in production - ideally on Kubernetes via Strimzi - including upgrades, topic/partition management, performance tuning, and TLS/secret rotation.
  • Distributed Processing (Strong Plus): Production experience operating one or more of Spark, Flink, or Ray - resource tuning, checkpointing, failure recovery.
  • Stateful Systems (Must Have): Production experience with Redis (clustering, persistence, failover) and a solid understanding of operating stateful workloads on Kubernetes (StatefulSets, PVCs, probes, operators).
  • Data Warehouses: Familiarity operating against Snowflake, BigQuery, or similar, and an understanding of JDBC connectivity and sink reliability.
  • Kubernetes & EKS: Strong hands-on EKS - cluster creation, scaling, version upgrades, and operator management.
  • Infrastructure as Code: Advanced proficiency with Terraform.
  • Programming: Proficiency in Python (or similar) for automation and tooling. Comfort reading and debugging JVM-based systems is a strong plus.
  • Reliability Mindset: Demonstrated ownership of incident management, RCA, capacity planning, and performance tuning for high-throughput systems.
  • CI/CD: Solid understanding of CI/CD methodology (Jenkins, GitHub Actions, or GitLab CI) for containerized and non-containerized apps. Supporting, not the core of the role.
Responsibilities
  • Streaming & Data Plane Reliability: Own the health of our Kafka-based runtime (managed via Strimzi on Kubernetes) - broker health, topic lifecycle and count management, partition and throughput tuning, certificate/secret rotation, and version upgrades - at a scale of hundreds of thousands of topics and hundreds of billions of rows per day.
  • Distributed Processing Engines: Operate and tune distributed system workloads in production in collaboration with backend teams, resource allocation, autoscaling, checkpointing, backpressure, and failure recovery for both batch and streaming jobs.
  • Stateful Services: Run Redis clusters and other stateful systems reliably - failover, persistence, liveness/readiness tuning, and capacity planning under heavy and bursty load.
  • Kubernetes & Operators: Take end-to-end ownership of Amazon EKS, Google GKE and the operators (Strimzi and others) running our stateful data workloads - cluster lifecycle, scaling, version upgrades, and resource governance.
  • Observability: Build deep, data-aware monitoring - consumer lag, throughput, partition skew, job latency, error rates - not just host and CPU metrics. Make the data plane's behavior legible before it breaks.
  • Incident Management: Lead root-cause analysis for distributed-systems failures (broker outages, crashloops, sink decommissions, control-plane race conditions) and drive durable fixes. Mitigate fast, but design out the recurrence.
  • Infrastructure as Code & Automation: Provision and manage cloud infrastructure with Terraform; build operational runbooks and automation, including for air-gapped / private enterprise installs (pre-staged images, operator-facing procedures).
  • Collaboration: Partner with platform, runtime, and connector engineering - and with SREs and support - to ship and scale new data-movement features reliably in a large-scale Linux environment.r with SREs, L2/Support, and developers to deploy and scale new product features and improve production monitoring in a large-scale Linux environment.
Desired Qualifications
  • Configuration management (Ansible preferred)
  • AWS services (IAM, VPC, EC2, S3, Lambda)
  • AWS CloudFormation
  • Soft Skills: Excellent communication and organizational skills; ability to coordinate effectively within a team and with customers

Nexla provides an enterprise-grade, AI-powered data integration platform that turns data from any source into production-ready data products for AI applications. It uses a no-code/low-code interface to unify data integration, preparation, governance, and monitoring, with 700+ pre-built connectors and support for ELT, ETL, streaming, APIs, and Retrieval-Augmented Generation (RAG). Its Nexsets concept creates virtual, human-readable data products with semantic metadata, data quality checks, and lineage to enable collaboration across technical and non-technical users. It can be deployed as SaaS, in hybrid multi-cloud environments, or on-premises, processes over a trillion records per month, and aims to reduce data deployment times from months to days by delivering ready-to-use data for AI agents.

Company Size

51-200

Company Stage

Series B

Total Funding

$33.5M

Headquarters

San Mateo, California

Founded

2016

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Simplify Jobs

Simplify's Take

What believers are saying

  • Microsoft 365 Copilot partnership, announced November 18, 2025, expands distribution into enterprise workflows.
  • Vespa.ai partnership, announced February 18, 2026, positions Nexla inside real-time RAG infrastructure.
  • Tripadvisor’s GTC 2026 demo validates Nexla as a production data layer for AI planning.

What critics are saying

  • Databricks, Snowflake, and Microsoft bundle adjacent integration features, compressing Nexla’s pricing power.
  • MCP Studio’s success depends on enterprises trusting autonomous access to Salesforce, SAP, and ServiceNow.
  • A stalled enterprise AI rollout would strand Nexla’s agentic pivot and expose its niche platform strategy.

What makes Nexla unique

  • Nexla’s June 9, 2026 MCP Studio builds governed MCP servers across 600+ systems.
  • Nexsets turn raw enterprise feeds into human-readable, metadata-rich data products.
  • Nexla’s 1,000+ connectors and hybrid ETL, ELT, streaming, and APIs unify integration.

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Benefits

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

-4%

1 year growth

0%

2 year growth

1%
Yahoo Finance
Jul 28th, 2026
Nexla surpasses 1,000 enterprise connectors to bridge data layer gap for AI agent deployments

Nexla has surpassed 1,000 bidirectional enterprise connectors, spanning databases, SaaS applications, file systems, streaming platforms, large language models, and vector stores. The company positions itself as the data layer for enterprise AI. Nexla's connector library provides AI agents with pre-built, managed access to enterprise systems. Each connector supports read and write functions, allowing agents to retrieve data and execute actions. The company pairs this with MCP Studio, which builds governed, task-specific MCP servers for individual business processes. The platform connects to MCP-compatible applications and agent frameworks, including Claude, ChatGPT, Gemini, and Microsoft Copilot. Every connector request undergoes identity verification, with all agent actions logged for audit purposes. Nexla serves clients including Johnson & Johnson, DoorDash, and American Express, processing over 1 trillion records monthly.

Associated Press
Jun 9th, 2026
Nexla launches MCP Studio to build task-specific AI agent servers across 600+ enterprise systems

Nexla has launched MCP Studio, a solution enabling organisations to build task-specific Model Context Protocol servers across enterprise systems through conversational setup. The platform is now available through an early access programme. MCP Studio addresses the challenge of enterprise workflows spanning multiple applications by creating servers that mirror business processes rather than individual systems. Users describe desired business outcomes and provide system access, whilst Nexla autonomously discovers data, selects necessary tools and generates production-ready servers. The platform connects to over 600 enterprise systems including Salesforce, Snowflake, SAP and ServiceNow, offering 10,000 available tools. It includes built-in governance through access controls, credential management and audit logging, and works with MCP-compatible applications including Claude, ChatGPT and Microsoft Copilot.

PhocusWire
Mar 26th, 2026
Tripadvisor demos AI planning tool.

Tripadvisor demos AI planning tool. Tripadvisor recently partnered with Nvidia, Nebius and Nexla to show what the future of end-to-end travel planning could look like with artificial intelligence (AI). The company is looking for ways to streamline travel planning - to make it simpler, smarter and more personalized, Rahul Todkar, vice president and head of data and AI for Tripadvisor, wrote on LinkedIn. In a live demonstration at Nvidia GTC 2026, attendees inserted an influencer's video into an experimental tool on Tripadvisor's native AI experience, he wrote. The tool found locations and experiences featured in the video, cross-referenced them with Tripadvisor's data and created a personalized itinerary that was "ready-to-book" for the user, according to Todkar. "Planning a trip is exciting...but it's also complex," Todkar wrote, sharing a demo video. "Hours (sometimes weeks) go into researching and sorting through ideas, options and prices across dozens of sources. As AI and agentic workflows evolve, our teams have been experimenting, testing and iterating on ways to make that process easier." Todkar told PhocusWire Tuesday that Tripadvisor offered the travel focus, Nvidia served as the model provider layer, Nibius provided the backbone and Nexla offered data integration. "Knowledge and expertise is what really is the key here." While Todkar said it wasn't that hard to pull the feature together, he did identify a couple challenges. Video processing, for example, proved to be difficult. "Understanding the right context, meaning out of the videos and then mapping that to our existing POIs [points of interest]... all the things we have on our site... connecting those two dots was the number one challenge," he said. Personalization was another hurdle, according to Todkar, who said the company has been performing specific experiments to learn more about both. Testing and experimentation comes next. "We do explore and do a lot of pilots on our site, especially with our AI-focused chip planning application," Todkar said. "This will be one of those features. We'll try to test and see what the user response is." If all goes well, the feature can be pushed into live production. Last year, Expedia Group debuted its AI-powered Trip Matching feature, which allows users to turn Instagram Reels into bookable itineraries. When asked about the similarity between the two initiatives, Todkar said he's seen early versions of the feature. He said the concept is the same but the execution might be a little different. "Inspiration can come from anywhere," he said. "More and more inspiration is your social media, your AI platforms, your top of the funnel. What users are increasingly telling us is they want to take that inspiration into trip planning, then booking." Inspiration to planning to booking has to become seamless. "All brands, I'm sure, are thinking about that," he said. "The differentiation becomes, how do you bring your own data? How do you bring your own personalization? And how do you drive actions faster?" Todkar said Tripadvisor is pushing further into AI-first features. "This is one of those features," he said. "There's a lot more we have in the hopper, and this is just an exciting space to be in."

Associated Press
Feb 18th, 2026
Nexla and Vespa.ai partner to streamline real-time AI search across 500+ enterprise data sources

Nexla, an AI-powered data integration platform, has partnered with Vespa.ai to simplify real-time AI search across enterprise data sources. The collaboration addresses a critical challenge in AI application development: connecting and preparing data from hundreds of disparate sources before powering intelligent search systems. Nexla offers over 500 pre-built connectors that transform data from various enterprise systems into production-ready formats, whilst Vespa provides distributed search, vector retrieval and real-time inference capabilities. The partnership includes two new integrations: a Vespa Connector in Nexla for seamless data piping, and a Vespa Nexla Plugin CLI that automatically generates application packages. The solution targets organisations building AI search, retrieval-augmented generation applications and high-throughput systems serving billions of documents with real-time updates.

The Manila Times
Feb 18th, 2026
Nexla and Vespa.ai Partner to Simplify Real-Time AI Search Across Hundreds of Enterprise Data Sources

Nexla and vespa.ai partner to simplify real-time AI search across hundreds of enterprise data sources. By GlobeNewswire February 18, 2026 Native integrations reduce setup time and ongoing maintenance by making it easy to ingest, index, and continuously update data from enterprise systems SAN MATEO, Calif., Feb. 18, 2026 (GLOBE NEWSWIRE) - Nexla, the enterprise-grade AI-powered data integration platform for agents, today announced a strategic partnership with Vespa.ai, the creator of the leading AI search platform for building and deploying large-scale, real-time AI applications. The partnership eliminates one of the biggest bottlenecks in AI application development: getting production-ready data into scalable, high-performance AI search and retrieval systems. Organizations building AI-powered applications face a critical challenge: connecting and preparing enterprise data from hundreds of disparate sources before it can power intelligent search and retrieval. This data variety - structured/unstructured, batch/ streaming, modern/ legacy, creates complexity that slows AI deployment to production. With over 500 pre-built connectors, Nexla addresses this challenge by transforming data variety from any enterprise system into production-ready data products for AI and agents, while Vespa provides the distributed search, vector retrieval, and real-time inference capabilities required to serve AI-powered applications at scale. Together, they create a seamless path from raw enterprise data to intelligent, production-grade AI search. As part of the partnership, Nexla launched native Vespa integrations that make working with Vespa faster and simpler: * Vespa Connector in Nexla: Seamlessly pipes data from sources such as Amazon S3, PostgreSQL, Snowflake, APIs, and even existing vector databases directly into Vespa, without custom code or complex configurations. * Vespa Nexla Plugin CLI: Automatically generates draft Vespa application packages, including schema files, directly from Nexla's metadata-defined data products (Nexsets), dramatically reducing setup time and configuration errors. Advertisement These capabilities enable teams to migrate from other vector databases, sync operational databases into Vespa, or continuously update Vespa indexes using batch, streaming, or CDC pipelines, all without writing code. The combined solution is especially valuable for organizations building or scaling: * AI search and RAG applications requiring hybrid retrieval across vectors, keywords, and structured filters * High-throughput, low-latency systems serving billions of documents with real-time updates * Complex ranking and inference pipelines, including multi-phase ranking and LLM integration Advertisement Nexla prepares and governs the data; Vespa executes advanced retrieval, ranking, and inference where the data lives. "Data integration and intelligent retrieval are two sides of the same coin in modern AI architectures," said Saket Saurabh, CEO and Co-Founder of Nexla. "Nexla unlocks data variety, transforms it, and delivers enterprise-grade, ready-to-use data products; Vespa.ai makes that data searchable and actionable in real time. This partnership creates a powerful combination for organizations building agentic RAG, recommendation systems, and AI-powered search at scale. Together, we're removing the friction between data preparation and intelligent retrieval, so teams can focus on building transformative AI experiences instead of wrestling with data plumbing." "Vespa is built for teams that need precision, performance, and real-time control at scale," said Jon Bratseth, CEO of Vespa.ai. "By partnering with Nexla, we're removing friction between data preparation and real-time execution, so teams can move from raw enterprise data to production-grade AI search and RAG systems faster and with far more control." https://www.nexla.com/nexla-vespa-ai About Nexla Nexla is an enterprise-grade, AI-powered data integration platform for agents that unlocks data from any source and transforms it into production-ready data products for AI and agents. With support for 500+ pre-built connectors and multiple integration styles - including ELT, ETL, streaming, APIs, and agentic RAG. Nexla enables teams to build and manage data flows without writing code. Trusted by leading enterprises, Nexla processes over one trillion records per month across industries. Learn more at nexla.com. About Vespa.ai Vespa.ai is a powerful platform for developing real-time search-based AI applications. Once built, these applications are deployed through Vespa's large-scale, distributed architecture, which efficiently manages data, inference, and logic for applications handling massive datasets and high concurrent query rates. Vespa delivers all the building blocks of an AI application, including vector database, hybrid search, retrieval augmented generation (RAG), natural language processing (NLP), machine learning, and support for large language models (LLM) and vision language models (VLM). It is available as a managed service and open source. Learn more at vespa.ai. Media Contact Jayashree Rajan [email protected]