Enterprise Platform Engineer - AI Agents

About the Role

We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.

This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.

This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions — not people management or process.

Responsibilities

• Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
• Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
• Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
• Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
• Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
• Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
• Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
• Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.

Qualifications

• Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
• Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
• Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
• Advanced knowledge of Kubernetes and Terraform in production environments.
• Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
• Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
• Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
• Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
• Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
• Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
• Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
• Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Our Culture

Who we are:

Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.

How we work:

• We move Blitzy Fast: Time is both our company’s and our clients’ most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
• Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
• Passion for Invention: We’re pushing the frontier of what’s possible, requiring constant innovation and iteration.
• We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
• We believe in being ‘everyday athletes’: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for 

Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.

About the role

You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.

Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office

What you will do

Technology & product leadership

• Define and drive the technology vision, architecture and long-term platform roadmap.
• Oversee the architecture, design and delivery of highly scalable enterprise systems.
• Ensure engineering excellence, velocity and reliability across the product lifecycle.

Engineering & platform management

• Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
• Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
• Oversee operational effectiveness, including uptime, production reliability and cost optimisation.

Innovation & AI strategy

• Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
• Own the GenAI/LLM solutions architecture.
• Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
• Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
• Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.

Technical leadership

• A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
• Collaborate with executive leadership on business strategy, client requirements and product delivery.
• Build, mentor and scale high-performing engineering teams with a growth mindset.
• Establish a strong technology culture grounded in ownership, innovation and continuous learning.

What success looks like

• Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
• Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
• Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.

Qualifications & experience

• Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
• A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
• Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
• Proven leadership in defining and executing technology strategy and platform roadmaps.
• Extensive cloud-native engineering experience with Azure, AWS and GCP.

Technical expertise

• Strong full-stack engineering background (Java, Python, JavaScript frameworks).
• Expertise with JS frameworks such as React, Angular and Node.js.
• Experience building and scaling distributed systems and microservices.
• Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
• Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).

Behavioural & leadership competencies

• Product and delivery management expertise, end to end, including delivery and customer support.
• Excellent communication, with the ability to influence executive stakeholders.
• High technical proficiency combined with strong business acumen.
• Strong analytical and decision-making skills.

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

Job Title: Platform Engineer

Location: Bangalore(Onsite)

Experience Level: 3-8

Salary Range: 20-30LPA

Description:

Join a team building an AI-native enterprise platform that helps businesses make faster, smarter and more consistent operational decisions using AI, enterprise data and workflow automation.

Design and build the core platform for enterprise decision workflows. Develop reusable workflow and decision runtimes. Build scalable, cloud-native distributed systems and event-driven architectures. Design enterprise-grade APIs and platform services. Build integrations with systems such as SAP and Oracle. Develop secure multi-tenant services with authentication and RBAC. Build and manage AWS cloud infrastructure and deployment systems. Implement monitoring and observability for production systems. Support both cloud and on-premise deployments. Enable faster onboarding and deployment of new enterprise workflows.

Requirements:

- Strong hands-on experience with Python

- FastAPI

- PostgreSQL

- Docker

- AWS

- Practical experience with Redis

- Kafka/event streaming

- REST APIs

- CI/CD

- Git

- Good understanding of Kubernetes

- Distributed systems

- Event-driven architecture

- Enterprise SaaS

- Microservices

- Strong backend engineering fundamentals

- Ability to design scalable, reliable and production-ready systems

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Job Description: Lead - Cloud Engineering (AWS / Azure)

Role Title: Lead - Cloud Engineering

Experience Level: 10+ Years

Domain Focus: Healthcare AI & Cloud Infrastructure

Location: Remote

Job Overview

We are seeking an experienced Lead - Cloud Engineering with over 10 years of IT experience to lead our cloud strategy, architecture, and infrastructure teams. In this role, you will oversee end-to-end cloud deployment, multi-cloud migration, and scalable architecture designed to support cutting-edge Generative AI applications in the healthcare technology domain.

The ideal candidate brings deep technical expertise in both AWS and Azure, strong hands-on capability in cloud infrastructure, and proven leadership experience driving security, compliance, and team growth.

Key Responsibilities

Cloud Architecture & Migration

• Lead the architecture, design, and execution of cloud migrations, deployments, and modernizations across AWS and Azure environments.
• Drive Infrastructure as Code (IaC) standards using Terraform, CloudFormation, or Bicep to ensure scalable, automated infrastructure provisioning.
• Build high-availability, low-latency architectures optimized for data-intensive Generative AI and Machine Learning workloads.

Security & Healthcare Compliance

• Enforce healthcare security standards including HIPAA, HITRUST, SOC 2, and data governance best practices across all cloud assets.
• Implement Zero-Trust security, Identity Access Management (IAM), data encryption key management, and continuous vulnerability monitoring.

Leadership & Team Management

• Manage, mentor, and scale a high-performing team of DevOps, Cloud, and SRE Engineers.
• Drive Agile workflows, sprint planning, incident response frameworks, and SLA compliance.
• Collaborate closely with Data Engineering, AI/ML, and Software Product teams to align infrastructure with business roadmaps.

Operations & FinOps

• Establish cloud cost optimization strategies (FinOps) to manage computing costs associated with AI models and large-scale data processing.
• Manage monitoring, alerting, and telemetry frameworks (e.g., Prometheus, Datadog, CloudWatch) to ensure 99.99% uptime.

Key Requirements

• Experience: 10+ years of overall IT experience with at least 5+ years in a cloud leadership or lead architect role.
• Cloud Platforms: Advanced hands-on expertise with both AWS (e.g., EC2, S3, EKS, Bedrock, SageMaker) and Azure (e.g., AKS, Azure OpenAI, Blob, Virtual Machines).
• DevOps & IaC: Strong background in Terraform, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
• Domain Knowledge: Prior experience building or managing cloud environments within Healthcare, Life Sciences, or HealthTech is strongly preferred.
• AI/ML Familiarity: Experience supporting cloud infrastructure for machine learning pipelines, LLM deployments, or GPU compute management.
• Certifications (Preferred): AWS Certified Solutions Architect – Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).

Solid product experience and an educational background from Tier‑1 universities are preferred.

As a Senior AI Engineer, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities. 

In this role, you will: 

• Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance. 
• Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features. 
• Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability. 
• Work with SQL and NoSQL databases to implement efficient data models and service access patterns. 
• Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs). 
• Use AI powered engineering tools to improve development quality, speed, and productivity. 
• Mentor engineers, supporting them in technical planning, implementation, and best practices. 
• Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure. 
• Write unit and integration tests and participate in code reviews to uphold engineering excellence. 
• Investigate production issues, ensuring timely and effective solutions. 
• Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies. 

Who You’ll Work With 

You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction. 

What Makes You a Qualified Candidate 

(Nonnegotiable qualifications) 

• Bachelor’s degree in Computer Science or equivalent from a recognized institution. 
• 5+ years of experience in backend services, distributed systems, or data platform development. 
• Strong proficiency in Java, Go, or Python for service development. 
• Good understanding of design principles, distributed system patterns, and service framework. 
• Hands-on experience designing and developing RESTful APIs. 
• Experience with SQL and NoSQL databases and data modelling. 
• Strong debugging, problem solving, and troubleshooting skills. 
• Experience with modern containerization and orchestration tools such as Kubernetes. 
• Knowledge of public cloud platforms. 
• Experience with AI productivity tools (e.g., GitHub Copilot). 
• Ability to work independently, drive workstreams, and deliver high quality outcomes. 
• Strong communication and collaboration skills. 

What You’ll Bring 

(Preferred qualifications) 

• Familiarity with messaging systems such as Kafka. 
• Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs. 
• A track record of influencing design decisions and driving engineering best practices. 
• The ability to mentor engineers and guide them through design, planning, and execution. 
• A proactive mindset and comfort working in fast paced, dynamic environments. 
• Curiosity, adaptability, and a passion for building impactful AI-driven products. 

Platform Engineering Lead (For client company)

Location: Pune, India

Experience: 7+ years 

What Success Looks Like

• Engineering teams ship faster with confidence and built-in guardrails.
• Cloud cost, security, and reliability are predictable, measurable, and well-managed.
• CI/CD pipelines are trusted, standardized, and production-ready.
• Platform decisions reduce cognitive load instead of introducing unnecessary process. 

Scope & Expectations

This is a hands-on leadership role combining architecture and implementation.

You will:

• Build, not just review.
• Own the platform roadmap—not just infrastructure tickets.
• Act as a force multiplier for product engineering teams rather than becoming a bottleneck.
• Drive platform strategy while remaining deeply involved in execution.

Key Responsibilities

Platform & Cloud Architecture

• Own Zoop's platform and cloud architecture across GCP and AWS.
• Design reusable, opinionated platform patterns instead of one-off infrastructure.
• Build and evolve Zoop's Internal Developer Platform (IDP), including:
• Self-service environments
• Golden paths (paved roads)
• Standardized templates
• Built-in engineering guardrails
• Lead Kubernetes and cloud-native adoption at scale.
• Drive infrastructure automation using Terraform, Pulumi, or similar Infrastructure-as-Code (IaC) tools.

CI/CD, Reliability & Developer Experience

• Establish robust CI/CD practices with quality gates and production readiness.
• Improve deployment safety through automation and testing.
• Define and monitor:
• Golden Signals
• SLIs
• SLOs
• Incident response processes
• Reduce operational toil and improve developer productivity.
• Make observability a first-class capability using cost-efficient monitoring systems.
• Build an observability platform that multiple engineering teams can easily integrate into their applications.

Security, Privacy & Compliance

• Build security-by-default into infrastructure and deployment pipelines.
• Lead implementation and continuous compliance for:
• DPDP Act (India)
• ISO 27001:2022
• SOC 2 Type II
• Implement:
• Zero Trust architecture
• Least-privilege access
• Secure data isolation

FinOps & Cloud Optimization

• Make cloud costs transparent and accountable across engineering teams.
• Establish FinOps practices including:
• Budgets
• Cost alerts
• Optimization routines
• Drive build-vs-buy decisions using clear ROI analysis.

AI, Data & MLOps Foundations

• Build secure and scalable foundations for AI and MLOps workloads.
• Define guardrails for AI systems and sensitive data handling.

Leadership & Collaboration

• Partner closely with engineering teams to align infrastructure strategy with product goals.
• Mentor engineers and guide teams through technical change.
• Balance long-term platform initiatives with practical execution.

What We're Looking For

Experience

• 7+ years of experience building and operating production infrastructure.
• Experience scaling engineering platforms in high-growth or regulated companies.
• Strong hands-on expertise in:
• Kubernetes and the cloud-native ecosystem
• Service Mesh technologies
• Policy Engines
• GCP, AWS (Azure exposure is a plus)
• Terraform and Infrastructure as Code

Engineering & Operations

• Strong understanding of SDLC and modern CI/CD systems (Jenkins, GitOps, etc.).
• Experience with observability tools such as:
• Grafana
• Prometheus
• New Relic
• Comfortable reading and contributing to production systems written in:
• Go
• Python
• Node.js

Security & Compliance

• Practical experience implementing ISO 27001 and SOC 2 controls.
• Strong understanding of:
• Data protection
• Privacy
• Identity and access management
• Security best practices

Mindset

We're looking for someone who is:

• Action-oriented with sound engineering judgment.
• Analytical, cost-conscious, and reliability-focused.
• Collaborative, calm under pressure, and open to feedback.
• Comfortable challenging decisions and explaining trade-offs when necessary.

Nice to Have

• Experience in fintech, identity, or other regulated industries.
• Built Internal Developer Platforms (IDPs) or shared infrastructure tooling.
• Contributions to open-source projects.

About the Team

SecurITe’s mission is to build an Agentic-AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for an exceptional Platform Engineer to help lead the development of our next-generation cybersecurity AI platform. This is a rare opportunity to shape how agentic AI transforms the future of cyber defense.

As a Platform Engineer, you will design, build, and operate the foundational infrastructure, deployment systems, and developer platforms that power our cybersecurity products across cloud and on-premise environments. You will work at the intersection of infrastructure engineering, cloud-native technologies, automation, reliability, and security to enable scalable and resilient product delivery.

You’ll collaborate closely with AI/ML, backend, security, QA, and product engineering teams to create self-service platforms, deployment pipelines, observability systems, and operational tooling that accelerate innovation while maintaining enterprise-grade reliability and security.

This role is ideal for Linux platform engineers and system specialists who excel at solving complex system challenges, automating wherever possible, and building resilient platforms that enable teams to move faster with confidence.

Why This Role Matters

Cybersecurity is undergoing a fundamental shift. AI is no longer an enhancement—it’s becoming the core engine of how detection, investigation, and response are executed. As our Platform Engineer, you will architect and build the infrastructure, automation, deployment, and operational systems that make this transformation real.

Your work will directly influence the scalability, reliability, and security of our AI-driven cybersecurity platform across both cloud and enterprise on-premise deployments. You’ll help establish the operational backbone that enables rapid innovation, secure product delivery, and resilient large-scale deployments in mission-critical environments.

This is a chance to solve novel technical challenges involving distributed systems, hybrid infrastructure, observability, automation, and secure software delivery while shaping how defenders outpace modern attackers.

What You’ll Do

●    Design, build, and own AWS infrastructure from the ground up (VPC architecture, EC2 fleet management, IAM, networking, security groups)

●    Administer and harden AlmaLinux VMs across production, staging, and dev environments

●    Build automation for provisioning, patching, and configuration management (infrastructure-as-code, config management tooling)

●    Design and implement observability: monitoring, logging, alerting, and on-call-worthy SLAs from scratch

●    Lead incident response — diagnosis, RCA, and post-incident documentation — with no dedicated ops team to escalate to

●    Make and document build-vs-buy and architecture decisions as the product and team scale

●    Work directly with founders/engineering to translate ambiguous asks into scoped technical plans

Impact You’ll Have

●    Accelerate engineering velocity through scalable developer platforms and automation

●    Improve deployment reliability, platform uptime, and operational efficiency

●    Enable secure and scalable AI-driven cybersecurity workloads

●    Reduce operational overhead through infrastructure automation and self-service systems

●    Help establish enterprise-grade cloud and on-premise deployment capabilities

●    Enhance product resiliency, observability, and operational excellence

●    Shape the long-term platform architecture powering next-generation cybersecurity products

●    Enable rapid and secure delivery of critical security innovations to customers

Required Experience

●    4+ years hands-on Linux administration (RHEL-family strongly preferred — AlmaLinux, CentOS, RHEL)

●    Deep Linux internals: systemd, networking, storage/LVM, process/resource management, kernel-level troubleshooting

●    Real AWS architecture experience — not just operating existing infra, but designing it (VPC, EC2, IAM, security groups, networking)

●    Demonstrated ability to scope and solve ambiguous problems independently, without a runbook or senior engineer to defer to

●    Scripting/automation proficiency (Python and/or Bash) beyond one-off scripts — built tooling that runs unattended

●    Track record of end-to-end ownership: has designed, built, and operated a system (not just contributed to one)

●    Clear, proactive communicator — documents decisions and explains reasoning without being asked

Required Skills & Qualifications

●    Strong Linux system administration and troubleshooting skills

●    Redhat certifications

●    Strong understanding of networking fundamentals, security, and distributed systems

●    Proficiency with Docker, and container orchestration

●    Experience with Terraform, Ansible, or similar infrastructure automation tools

●    Strong scripting or programming skills in Python, Bash, or Go

●    Knowledge of observability tools such as Prometheus, Grafana, ELK, or OpenTelemetry

●    Understanding of platform security best practices and secure infrastructure design

●    Familiarity with virtualization technologies and hybrid infrastructure environments

●    Strong problem-solving and debugging abilities

●    Excellent communication and collaboration skills

●    Ability to thrive in fast-paced startup environments

Nice to Have

●    Configuration management/automation at scale (Ansible, AWX, Terraform, or similar)

●    Monitoring/observability stack experience (Prometheus, Grafana, Zabbix, ELK, Datadog)

●    Container experience (Docker; Kubernetes a plus but not core to this VM-based stack)

●    Experience in a startup or small-team environment where infra was built from scratch

●    Security/compliance exposure (vulnerability remediation, hardening, SSO/access control)

The Mindset

Problem Solver

You thrive on complex, ambiguous challenges and engineer elegant solutions.

Ownership-Driven

You take initiative, move fast, and deliver outcomes without hand-holding.

Continuous Learner

You stay ahead of the curve in AI, ML, cloud-native technologies, and emerging infrastructure trends.

Startup DNA

You excel in fast-moving environments where priorities evolve and impact is immediate.

Read This Before Anything Else

We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.

About CraftMyPlate

CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.

Where We Stand

Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.

Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.

The Technical Reality

Here's an honest read of the engineering problem, not a sanitized version of it.

Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.

Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.

The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.

You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.

Why This Role Exists

You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.

If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.

What You'll Own

• Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
• Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
• The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
• The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
• Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
• Technical accountability. When something breaks, you fix it. You don't escalate and wait.

Our Stack, and the Depth We Expect

Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.

Go deep here. This is where the real architecture decisions live, and where the business impact is highest:

• AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
• TypeScript, our primary language across backend and frontend.
• Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.

Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.

This Is You If

• You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
• You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
• You've made engineers around you measurably better, whether or not you've held the title for it yet.
• You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
• You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
• You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.

This Might Not Be the Right Fit If

• You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
• You'd rather receive direction than bring us architecture and AI strategy yourself.
• You haven't yet gotten hands-on with AI coding tools in your daily work.
• You're drawn more to the title than the work behind it.

If none of that sounds like you, we'd love to hear from you.

Requirements

• 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
• Prior experience leading or mentoring engineers, formally or informally.
• Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
• Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.

Compensation

Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.

If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.