Who We Are:
Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai. 

About the Role - Staff Engineer – Software Development.

Our SaaS platform serves enterprise customers with a reliable, secure, and scalable product built on modern microservices, event-driven data pipelines, and increasingly, AI-powered capabilities.

We are seeking a Staff Engineer – Software Engineering to join our SaaS Platform team. Staff Engineers at Aviatrix operate at the intersection of technical depth and cross-team influence. You will drive the design and delivery of complex backend systems — including AI-augmented data pipelines and agentic AI integrations — while raising the technical bar across the organization. This role is ideal for an engineer who is deeply technical, thrives on solving ambiguous problems, and is ready to shape both the platform’s architecture and the team’s engineering culture.

Position Responsibilities

Architecture & Technical Leadership

• Lead the architecture and delivery of complex backend platform features spanning multiple microservices; break down large, ambiguous projects into well-scoped sub-projects and guide senior engineers through execution.
• Define technical standards, patterns, and best practices for backend microservices development across the team — covering API design, service communication, data modeling, and reliability.
• Own the architectural design of AI-augmented data pipelines: integrating model inference, agentic workflows, and LLM-based processing steps into streaming and batch data flows on AWS.
• Evaluate and recommend agentic AI frameworks and tooling (such as LangChain, LlamaIndex, Amazon Bedrock Agents, or equivalent) for use in platform components; establish integration patterns the broader team can follow.
• Write and present comprehensive design documents and technical proposals that articulate complex problems, solution trade-offs, and long-term platform direction.
• Drive improvements to Aviatrix’s product and security posture, including contributions outside your immediate project area.

AI-Augmented Data Pipelines

• Design and implement data pipelines that incorporate AI/ML model inference as a first-class processing step, enabling intelligent enrichment, classification, anomaly detection, and summarization of platform telemetry and events.
• Architect agentic AI workflows that operate autonomously within data pipelines — orchestrating tool use, retrieval-augmented generation (RAG), and multi-step reasoning to drive platform automation.
• Integrate large language models (LLMs) and foundation models via managed APIs (Amazon Bedrock, OpenAI, Anthropic) and self-hosted inference endpoints into backend services and pipeline stages.
• Build robust prompt engineering and context management layers that make AI model calls reliable, observable, cost-efficient, and safe in a production SaaS context.
• Establish guardrails, evaluation frameworks, and monitoring strategies for AI components in pipelines — including output validation, hallucination detection, latency tracking, and cost controls.
• Collaborate with data and ML teams to define feature stores, embedding pipelines, vector database integrations (e.g., Amazon OpenSearch, pgvector), and model lifecycle management practices.

Backend & Microservices Engineering

• Design and implement high-performance, production-grade microservices in Golang using gRPC and REST; ensure services are secure, observable, and operationally resilient.
• Drive the design of event-driven architectures using AWS data pipeline services — Kinesis, MSK (Kafka), Glue, Step Functions, and EMR — to support real-time and batch processing at scale.
• Enforce strong security and networking practices: AWS VPC architecture, IAM least-privilege access, PrivateLink for private service connectivity, and encryption in transit and at rest.
• Lead platform-wide reliability initiatives: SLO definition, distributed tracing, structured logging, alerting, and chaos engineering practices.
• Conduct rigorous design and code reviews; set a high bar for correctness, testability, and operational readiness.

Team Influence & Collaboration

• Serve as a technical anchor for the team — raising engineering quality through mentorship, design guidance, and a culture of rigorous technical thinking.
• Collaborate with product management and leadership to align technical roadmap investments with business priorities and customer needs.
• Partner with senior engineers across teams to drive consistency in platform architecture and avoid redundant solutions.
• Provide expert guidance during escalations and critical production incidents; drive root-cause analysis and long-term remediation.
• Contribute to recruiting and interviewing; help define bar-raising standards for backend and AI engineering roles.

Requirements

Experience & Education

• 7–10+ years of professional software engineering experience, with a strong track record of technical leadership on backend systems.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• Demonstrated experience designing and operating SaaS or PaaS products at scale, with multi-tenancy and high-availability requirements.
• Strong foundation in data structures, algorithms, operating systems, and distributed systems.
• Experience working in fast-paced, high-growth technology companies with geographically distributed teams.

Backend & Microservices

• Strong proficiency in Golang; experience building production-grade gRPC-based microservices.
• Deep understanding of distributed systems: consistency, fault tolerance, service discovery, back-pressure, and distributed tracing.
• Expertise in RESTful and gRPC API design, with a strong sense of API contracts, versioning, and backward compatibility.
• Experience building event-driven architectures with message queue and streaming systems (Kafka/MSK, Kinesis, SQS/SNS).
• Strong understanding of elegant and robust system design; ability to evaluate and articulate key engineering trade-offs.

Agentic AI & LLM Integration

• Hands-on experience integrating large language models (LLMs) and foundation models into production backend systems via managed APIs or self-hosted inference.
• Practical knowledge of agentic AI concepts: tool use, autonomous multi-step reasoning, agent orchestration, and human-in-the-loop patterns.
• Experience with at least one agentic AI framework or platform (e.g., LangChain, LlamaIndex, Amazon Bedrock Agents, AutoGen, or similar).
• Familiarity with retrieval-augmented generation (RAG): embedding models, vector databases (OpenSearch, pgvector, Pinecone), and context retrieval strategies.
• Understanding of prompt engineering principles: structured prompts, few-shot examples, chain-of-thought reasoning, and output validation.
• Experience designing AI guardrails and evaluation pipelines to ensure reliability, safety, and cost-efficiency of LLM components in production.

Data Pipelines

• Proven experience designing and operating large-scale data pipelines for real-time streaming and batch workloads.
• Strong working knowledge of AWS data pipeline services: Amazon Kinesis (Data Streams & Firehose), AWS Glue, Amazon MSK, AWS Step Functions, and Amazon EMR.
• Ability to embed AI/ML inference steps — including LLM calls, embedding generation, and model scoring — as processing stages within data pipelines.
• Familiarity with pipeline observability: data lineage, quality monitoring, SLA management, and alerting.
• Experience with schema management, data quality enforcement, and data catalog practices (e.g., AWS Glue Data Catalog).

AWS & Cloud Infrastructure

• Deep experience with AWS as a primary cloud platform; strong understanding of high-availability, multi-AZ deployment patterns.
• Solid knowledge of AWS networking and security: VPC architecture, IAM roles and policies, AWS PrivateLink, Transit Gateway, and security groups.
• Proficiency with Kubernetes (EKS), including workload scheduling, RBAC, networking (CNI), and cluster operations.
• Experience with infrastructure-as-code (Terraform, CDK, or CloudFormation) and CI/CD pipelines for cloud-native backend services.
• Familiarity with Amazon Bedrock or equivalent managed AI/ML platforms for model deployment and inference at scale.

Nice to Have

• Experience fine-tuning or adapting foundation models for domain-specific tasks.
• Familiarity with ML frameworks (PyTorch, HuggingFace Transformers) and model serving infrastructure (SageMaker, TorchServe).
• Background in network security, cloud networking, or SASE/SD-WAN technologies.
• Experience with multi-cloud environments (Azure, GCP) alongside AWS.
• Contributions to open-source AI, data engineering, or cloud-native projects.

Interpersonal & Communication

• Excellent written and verbal communication; able to produce clear technical documents and present confidently to engineering and product leadership.
• Demonstrated ability to lead through influence, build consensus across teams, and drive outcomes without direct authority.
• Team player who thrives in collaborative, geographically distributed environments and startup-paced cultures.

 
Who We Are:
Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai. 

About the Role - Staff Engineer – Backend Engineering

Aviatrix PaaS delivers intelligent, multi-cloud network and security services as a managed offering. We are seeking a Staff Engineer – Backend Engineering to lead the design and delivery of Golang-based microservices, large-scale data engineering pipelines, and enterprise SaaS platform operations on AWS. You will set technical direction, raise the engineering bar across the team, and drive platform reliability and scalability at enterprise scale.

Position Responsibilities

Architecture & Technical Leadership

• Own the end-to-end architecture and delivery of major backend platform capabilities; break down complex problems into well-scoped engineering efforts and guide execution.

• Define next-generation architectures for distributed Golang microservices and high-throughput data pipelines on AWS; establish standards the broader engineering org adopts.

• Write design proposals and technical documents that articulate trade-offs and long-term platform direction for engineering and product leadership.

• Drive improvements to platform reliability, security posture, and engineering quality across the team.

Golang Microservices Engineering

• Lead design and implementation of production-grade Golang microservices; establish team-wide service patterns, API conventions, and coding standards.

• Architect synchronous (gRPC, REST) and asynchronous (event-driven) inter-service communication with a focus on fault tolerance and operational simplicity.

• Drive SLO/SLA definition, distributed tracing, structured logging, alerting, and capacity planning across the microservices estate.

• Set a high bar through rigorous design and code reviews; mentor engineers on idiomatic Golang, testability, and production readiness.

Data Engineering & Pipelines

• Architect and deliver large-scale data engineering pipelines for real-time streaming and batch workloads, with a focus on reliability, throughput, and data quality.

• Own adoption and integration of AWS data pipeline services: Amazon Kinesis, Amazon MSK (Kafka), AWS Glue, AWS Step Functions, and Amazon EMR.

• Define pipeline reliability standards: idempotency, dead-letter queue handling, delivery semantics, schema governance, and back-pressure management.

• Establish pipeline observability practices: throughput/latency dashboards, data quality monitoring, lineage tracking, SLA alerting, and cost-per-record analysis.

SaaS Platform Operations

• Drive SaaS-specific platform capabilities: multi-tenancy isolation, tenant-aware data partitioning, rate limiting, quota management, and resource fairness.

• Enforce AWS networking and security best practices: VPC architecture, IAM least-privilege, PrivateLink, Transit Gateway, and encryption in transit and at rest.

• Lead platform infrastructure-as-code practices (Terraform/CDK) and CI/CD pipeline standards for consistent, auditable deployments.

• Own the operational model: runbook standards, on-call practices, incident management, and post-incident review culture.

Team Leadership & Influence

• Mentor engineers and serve as a technical anchor for the team; foster a culture of rigorous technical thinking and continuous improvement.

• Partner with product management and leadership to align backend platform investments with business priorities and customer commitments.

• Lead escalations and critical production incidents; drive root-cause analysis and long-term remediation.

• Contribute to recruiting and interviewing; help define bar-raising standards for backend and data engineering hires.

Requirements

Experience & Education

• 6+ years of professional software engineering experience with a strong track record of technical leadership on large-scale backend systems.

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

• Demonstrated experience designing and operating enterprise-grade SaaS/PaaS products at scale: multi-tenancy, high availability, and operational reliability.

Golang & Microservices

• Expert proficiency in Golang; extensive experience building production-grade gRPC-based microservices.

• Deep expertise in distributed systems: consistency models, fault tolerance, service discovery, circuit breaking, and distributed tracing.

• Mastery of RESTful and gRPC API design, including versioning, backward compatibility, and API contract governance.

• Strong understanding of concurrent Golang programming: goroutines, channels, sync primitives, and memory management.

Data Engineering & Pipelines

• Deep, hands-on experience designing and operating large-scale data pipelines for real-time streaming and batch workloads in production.

• Expert knowledge of AWS data pipeline services: Kinesis, Amazon MSK (Kafka), AWS Glue, Step Functions, and EMR.

• Strong grasp of pipeline reliability patterns: idempotency, exactly-once semantics, dead-letter queues, and schema evolution.

• Experience with data storage technologies relevant to SaaS data engineering: Amazon S3, Redshift, Aurora/RDS, and DynamoDB.

AWS & SaaS Platform

• Deep expertise with AWS as a primary cloud platform; strong command of high-availability, multi-AZ deployment architectures.

• Advanced knowledge of AWS networking and security: VPC design, IAM, PrivateLink, Transit Gateway, and security group management.

• Proficiency with Kubernetes (EKS): scheduling, RBAC, networking (CNI), cluster operations, and multi-tenant workload isolation.

• Strong experience with infrastructure-as-code (Terraform, CDK) and mature CI/CD pipelines for cloud-native backend services.

Nice to Have

• Familiarity with data lakehouse tooling (Apache Iceberg, Delta Lake, AWS Lake Formation) or Amazon OpenSearch Service.

• Background in network security, cloud networking, or SASE/SD-WAN technologies.

• Experience with multi-cloud environments (Azure, GCP) alongside AWS.

Who We Are:
Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai. 

About the Role – Senior Member of Technical Staff – Software Development

Our SaaS platform serves enterprise customers with a reliable, secure, and scalable product built on modern microservices, event-driven data pipelines, and AI-powered capabilities.We are seeking a Senior Member of Technical Staff (Sr MTS) – Software Development to join our SaaS Platform team. This role is ideal for a backend engineer who has moved beyond writing individual features and is ready to take meaningful ownership of platform components, contribute to technical design, and start influencing the direction of the team. You will work alongside Staff and Principal Engineers on building microservices, data pipelines, and AI-integrated backend systems on AWS — developing both your technical depth and your ability to lead within a team.

Position Responsibilities: 

Feature Development & Ownership

• Take end-to-end ownership of backend features and services — from requirements and design through implementation, testing, deployment, and monitoring.
• Design and implement production-grade microservices in Golang, following team standards for gRPC and RESTful API patterns.
• Contribute meaningfully to technical design discussions; author design documents for features and components you own, incorporating feedback from senior engineers.
• Write well-tested, maintainable code; champion testing practices including unit, integration, and end-to-end tests within your feature area.
• Participate in on-call rotations; debug and resolve issues in distributed backend services and contribute to post-incident reviews.

Data Pipelines & AI Integration

• Build and extend data pipeline components that process, enrich, and route platform telemetry and events using AWS streaming and batch services (Kinesis, MSK, Glue, Step Functions).
• Integrate AI and LLM capabilities into backend services and pipeline stages — including model inference calls, output parsing, and result handling — under the guidance of Staff Engineers.
• Implement agentic AI workflow components such as tool-use handlers, retrieval-augmented generation (RAG) steps, and prompt orchestration layers as part of broader pipeline designs.
• Contribute to the reliability and correctness of AI pipeline components through thorough testing, output validation, and adherence to team guardrail standards.

Platform Reliability & Operations

• Ensure backend services you build are observable from day one: structured logging, metrics, distributed tracing, and alerting are treated as part of the definition of done.
• Apply AWS networking and security best practices in the services you build: secure IAM roles, VPC-aware service communication, and encryption in transit and at rest.
• Proactively identify and address reliability gaps, performance bottlenecks, and technical debt in platform components you own.
• Support deployment of services on AWS using team CI/CD pipelines and infrastructure-as-code tooling.

Collaboration & Team Contribution

• Collaborate effectively with Staff and Principal Engineers, product managers, and peers across a geographically distributed team.
• Conduct thorough code reviews and provide constructive, actionable feedback; help MTS engineers grow through mentorship on your area of expertise.
• Document APIs, service behavior, data flows, and runbooks clearly so teammates can understand, operate, and evolve your work.
• Participate actively in planning, estimation, and sprint ceremonies; raise technical risks and dependencies early.

Requirements

Experience & Education

• 3+ years of professional software engineering experience in backend development.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• Solid foundation in computer science fundamentals: data structures, algorithms, and operating systems.
• Demonstrated experience owning and shipping backend features or services in a production cloud environment.
• Experience working in collaborative, agile engineering teams; comfortable operating in fast-paced, high-growth environments.

Backend & Microservices

• Proficiency in Golang or a comparable strongly typed backend language; willingness to work primarily in Golang.
• Working understanding of microservices architecture: service boundaries, inter-service communication via REST and gRPC, and the trade-offs of distributed systems.
• Experience designing and implementing APIs with attention to correctness, reliability, and ease of use by other services.
• Familiarity with event-driven patterns and messaging systems such as Kafka, Kinesis, or SQS/SNS.
• Strong testing practices: unit, integration, and contract testing for backend services.

Agentic AI & LLM Integration

• Working knowledge of large language models (LLMs) and how they are integrated into backend systems via API calls (e.g., Amazon Bedrock, OpenAI, or Anthropic APIs).
• Familiarity with agentic AI concepts: tool use, multi-step reasoning, and agent orchestration frameworks such as LangChain, LlamaIndex, or Amazon Bedrock Agents.
• Ability to implement prompt templates, manage context windows, and handle model outputs reliably within backend service logic.
• Understanding of retrieval-augmented generation (RAG) patterns: embedding generation, vector store queries, and context injection into prompts.
• Awareness of production considerations for AI components: output validation, error handling, latency management, and cost awareness.

Data Pipelines

• Practical experience building or contributing to data pipelines for real-time or batch processing workloads.
• Familiarity with AWS data pipeline services: Amazon Kinesis, AWS Glue, Amazon MSK (Kafka), AWS Step Functions, or Amazon EMR.
• Understanding of how to embed AI/ML model inference calls as processing steps within a data pipeline.
• Ability to add pipeline observability: tracking throughput, latency, error rates, and data quality metrics.

AWS & Cloud Infrastructure

• Hands-on experience deploying and operating backend services on AWS; familiarity with core services including EC2, ECS/EKS, S3, RDS, and SQS/SNS.
• Basic understanding of AWS networking and security: VPC, security groups, IAM roles and policies, and encrypted communications.
• Experience with containerization (Docker) and deploying services in container-based environments.
• Comfort working with CI/CD pipelines, Git-based workflows, and infrastructure-as-code tooling (Terraform or AWS CDK is a plus).

Nice to Have

• Experience with Kubernetes (EKS) for container orchestration.
• Hands-on use of Amazon Bedrock or equivalent managed AI platforms for LLM inference.
• Experience with vector databases or embedding stores (OpenSearch, pgvector, Pinecone).
• Exposure to AWS managed data services such as Amazon Redshift, DynamoDB, or Aurora.
• Background in network security, cloud networking, or multi-cloud environments.
• Interest in or exposure to ML model lifecycle management and MLOps practices.

Interpersonal & Communication

• Clear written and verbal communication; able to write design documents, articulate technical decisions, and give constructive code review feedback.
• Collaborative team player who works well in cross-functional, geographically distributed teams.
• A growth mindset — eager to deepen expertise, take on new challenges, and mentor peers as you develop.

• Design, implement, test, and ship backend features and services that are reliable, well-documented, and maintainable.
• Build and extend microservices using Golang, following team conventions around gRPC and RESTful API design.
• Participate in the full development lifecycle — from requirements and design to code review, deployment, and monitoring.
• Write clean, well-tested code; contribute unit and integration tests and maintain high code quality standards.
• Debug and resolve issues in distributed backend services; participate in on-call rotations as you grow into the role.

• Collaborate closely with senior engineers, product managers, and peers to deliver platform features on time and with high quality.
• Actively participate in design and architecture discussions; bring curiosity and fresh perspectives to technical conversations.
• Incorporate feedback from code reviews to continuously improve your engineering skills and deepen your understanding of the platform.
• Document your work clearly — APIs, service behavior, runbooks — to help teammates understand and maintain what you build.
• Stay current with industry trends in backend development, cloud-native patterns, and distributed systems.

• Contribute to the reliability and observability of backend services by adding metrics, logs, and alerts as part of feature delivery.
• Assist in deploying and operating services on AWS cloud infrastructure, following team runbooks and operational standards.
• Help identify and address performance bottlenecks, reliability gaps, and technical debt in existing platform components.

• 1–3 years of professional software engineering experience in backend development.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• Solid grounding in computer science fundamentals: data structures, algorithms, and operating systems.
• Experience contributing to or shipping features in a production backend service or cloud application.

• Proficiency in at least one strongly typed backend language; experience with Golang is a strong plus.
• Understanding of microservices architecture — service boundaries, inter-service communication (REST/gRPC), and the trade-offs of distributed systems.
• Familiarity with API design principles: RESTful HTTP APIs, request/response patterns, and error handling.
• Working knowledge of relational or NoSQL databases; ability to write efficient queries and understand basic data modeling.
• Experience writing unit tests and integration tests; appreciation for testing as a quality practice.

• Hands-on experience building or deploying backend services on a public cloud platform, with AWS preferred.
• Familiarity with core AWS services used in backend applications: EC2, S3, RDS, SQS/SNS, or Lambda.
• Basic understanding of containerization (Docker) and how services are packaged and deployed.
• Comfort working with CI/CD pipelines and version control (Git) in a collaborative engineering environment.

• Experience with Golang and gRPC-based microservices.
• Exposure to event-driven or streaming architectures (Kafka, Kinesis, SQS).
• Familiarity with Kubernetes or container orchestration concepts.
• Experience with AWS managed data services: Kinesis, Glue, Step Functions, or MSK.
• Exposure to infrastructure-as-code tools such as Terraform or AWS CDK.
• Interest in or exposure to networking, cloud security, or multi-cloud environments.

• Clear written and verbal communication; able to articulate technical concepts to teammates and in code reviews.
• Collaborative mindset — you ask questions, share context, and contribute positively to team culture.
• Eagerness to learn, receive feedback, and grow quickly in a fast-paced, distributed team environment.

WHO WE ARE:
Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai. 

About the Role: Distinguished Engineer

Overview

We are seeking a Cloud AI Network Security Developer to architect and deliver advanced AI-driven network security capabilities across multi-cloud environments.

You’ll lead the design of Python/Go-based distributed systems that power intelligent firewalls, real-time telemetry analytics, and LLM-integrated threat automation.

This role combines deep knowledge of cloud networking, firewall technologies, data engineering, and AI model integration to create secure, adaptive, and self-learning security systems.

Key Responsibilities

• Lead the architecture, design, and development of advanced cloud networking solutions.
• Mentor and provide technical guidance to engineering teams, fostering a culture of innovation and excellence.
• Collaborate with cross-functional teams to develop and implement strategies that enhance cloud network performance, scalability, and security.
• Drive the adoption of new technologies and best practices in cloud networking.
• Conduct in-depth research and analysis to identify emerging trends and technologies in cloud networking.
• Present technical vision and roadmap to stakeholders, ensuring alignment with business goals.
• Contribute to the development of industry standards and participate in technical conferences and committees.

Required Skills

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• 15+ years of experience in software development and cloud networking.
• Deep understanding of cloud networking architectures, protocols, and technologies
• Proven experience in leading and mentoring engineering teams.
• Strong problem-solving skills and the ability to think strategically.
• Excellent communication and presentation skills.
• Demonstrated ability to drive innovation and influence industry standards.
• Solid experience in Kubernetes, microservices architecture, and observability systems (Prometheus, ELK, Grafana).
• Familiarity with security frameworks (Zero Trust, NIST CSF, CIS Benchmarks).

• Should have architected security and networking solutions, delivering key innovations.
• Patent holders in cloud networking or security are preferred.
• Must be hands-on, serve as a subject matter expert (SME), and provide both technical and thought leadership to a global team of engineers.
• Should have led large-scale initiatives across geographies within the company, including hackathons, idea generation, and driving successful implementation and delivery.
• Must possess up-to-date, hands-on expertise in AI technologies and their practical implementation.
• Should be able to code, debug, and provide effective fixes or solutions as needed.

Nice to Have

• Experience in LLM application design (RAG, LangChain, vector databases).
• Expertise with network telemetry analytics and visualization systems.
• Contributions to open-source network security or AI frameworks.
• Knowledge of distributed systems scaling, resilient cloud design, and multi-cloud policy federation.
• Certifications such as AWS Security Specialty, GCP Cloud Security Engineer, CISSP, or CKA.

WHO WE ARE:  

Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai.

ABOUT THE ROLE:

Senior MTS - Software Development Engineer

The Observability team delivers performant, resilient, and scalable solutions that power our observability platform. This infrastructure spans the full data lifecycle — collection, transmission, processing, storage, and analysis — underpinning Aviatrix's end-to-end multi-cloud networking solution.

We are looking for a Sr. Member of Technical Staff (Sr. MTS) to join the Observability team. In this role, you will independently solve technically difficult problems, contribute to platform architecture, and deliver impactful improvements to the security, quality, reliability, and performance of our observability systems.

KEY RESPONSIBILITIES

Technical Execution

• Design and implement solutions to a wide range of technically difficult problems across observability plane modules, using primarily Golang, Javascript and Python
• Deliver features and improvements independently; demonstrate initiative and sound technical judgment throughout the development lifecycle
• Write clean, testable, and maintainable code consistent with objectives set by Engineering leadership
• Develop imaginative, thorough, and practicable solutions that incrementally improve product security, quality, reliability, performance, and ease of operations for customers

Project Ownership & Planning

• Set milestones for assigned tasks and prioritize work to meet release schedules
• Proactively identify risks and communicate progress at critical checkpoints, ensuring soundness of technical judgment and overall accuracy of deliverables
• Work effectively under general supervision, with the ability to drive tasks to completion with minimal day-to-day guidance

Architecture & Design

• Apply and advance core technical standards, principles, and best practices in data pipeline development and observability infrastructure
• Participate actively in design and code reviews, providing constructive feedback that improves quality and shares knowledge across the team
• Evaluate and recommend approaches for collecting, transmitting, processing, and storing large-scale observability data in multi-cloud environments

Collaboration & Communication

• Engage frequently across organizational boundaries, representing the team in providing solutions to technical issues associated with specific projects or customer escalations
• Contribute actively to team and Engineering meetings; may participate in cross-functional teams
• Communicate technical decisions clearly — both in written documentation and verbal discussion — to engineering peers and stakeholders

Quality & Operational Excellence

• Contribute to improving test coverage, potentially beyond core project areas
• Participate in on-call rotations; take ownership of diagnosing and resolving production issues in observability systems
• Drive incremental improvements to engineering practices, including testing standards and operational runbooks

REQUIREMENTS

• 3+ years of relevant software development experience with a BS in Computer Science, Engineering, or a related field (or equivalent experience)
• Demonstrated ability to independently solve defined but technically difficult problems end-to-end
• Proficiency in Golang (strongly preferred) and/or Python
• Experience building and operating microservice-based architectures
• Strong knowledge of data pipeline development and ETL best practices
• Excellent software engineering fundamentals: clean, testable, well-documented code
• Strong communication skills — able to represent the team in technical discussions and customer-facing escalations
• Collaborative team player who thrives in startup-style environments

Preferred

• Prior experience with one or more Cloud Service Providers (AWS, Azure, GCP, OCI, Alibaba Cloud)
• Experience with nodejs and javascript backend UI development.
• Experience deploying and managing big data or streaming technologies (e.g., Kafka, Flink, Spark, ClickHouse) on Kubernetes
• Familiarity with observability tooling and standards (e.g., OpenTelemetry, Prometheus, Grafana, distributed tracing)

US Pay Range

The annual base salary range for this full-time position is $157,700-$185,500 + benefits + 401(k) match + equity and is bonus eligible. The pay range is determined by the role, work location, job-related skills, level, experience and relevant education.  The range displayed is applicable only for new hires for the listed position located in the US. Your Talent Advisor can share more details regarding salary ranges, benefits, and equity for your location during the hiring process.

#LI-RACHEL #LI-Remote

WHO WE ARE:  

Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai.

ABOUT THE ROLE:

The Aviatrix SRE team is a small but highly skilled global group of Systems Engineers/SREs dedicated to ensuring the reliability, availability, and performance of Aviatrix’s critical systems and services. Our mission is to build and maintain a robust, resilient infrastructure that enables Aviatrix to deliver high-quality services with agility through automation, best practices, and a culture of operational excellence.

As a Member of Technical Staff (MTS) Site Reliability Engineer, you’ll be developing your foundational SRE skills while contributing to the reliability and performance of our systems. You’ll work under supervision to implement solutions, learn our infrastructure, and gain hands-on experience with production systems.

KEY RESPONSIBILITIES

• Kubernetes: Learn to manage basic application deployments, assist with troubleshooting, and support monitoring tasks
• Infrastructure as Code: Implement IaC for straightforward provisioning tasks and configuration changes
• Automation & Development: Contribute to existing automation tools and frameworks in Golang and Python
• Basic System Maintenance: Contribute to system reliability through routine maintenance tasks and monitoring
• Implementation Support: Implement well-defined solutions for moderate complexity technical problems
• Reliability Engineering: Learn fundamentals of system reliability; contribute to maintaining uptime for well-defined services under guidance
• Automation Excellence: Execute basic automation scripts; contribute to existing automation frameworks with supervision
• Observability: Implement basic monitoring configurations; learn to read dashboards and interpret common metrics
• Incident Management: Participate in incident response with escalation support; document findings and learnings
• Performance Engineering: Monitor system performance using established metrics; escalate performance issues appropriately
• Collaboration: Participate actively in team meetings; communicate status and blockers effectively

QUALIFICATIONS

• Experience: 0-3+ years in software engineering, system administration, or related technical roles
• Education: BS in Computer Science, Engineering, or related field
• Programming: Basic proficiency in at least one programming language (Golang, Python preferred)
• Cloud Platforms: Foundational knowledge of cloud platforms (AWS, Azure, GCP)
• Linux: Basic Linux system administration skills
• Version Control: Experience with Git and code review processes
• Communication: Strong communication skills and eagerness to learn
• Problem-Solving: Demonstrated ability to solve technical problems independently

US Pay Range

The annual base salary range for this full-time position is $111,600-$131,300 + benefits + 401(k) match + equity and is bonus eligible. The pay range is determined by the role, work location, job-related skills, level, experience and relevant education.  The range displayed is applicable only for new hires for the listed position located in the US. Your Talent Advisor can share more details regarding salary ranges, benefits, and equity for your location during the hiring process.

#LI-RACHEL #LI-Remote