Cloud/Platform Architect (SRE)

What You Will Own 

Platform Architecture 

• Full architectural ownership of the non-AWS toolchain: CI/CD, observability, event streaming, automation, secrets, and deployment infrastructure 
• Define, build, and enforce platform standards across portfolio products 
• Terraform IaC for all infrastructure — nothing provisioned manually, everything versioned and reviewed 
• Self-service developer platform so product teams ship without waiting on platform 

Event Streaming & Pipeline Infrastructure 

• Own the event streaming architecture, operational standards, and health monitoring across all products using real-time pipelines 
• Design and maintain batch processing infrastructure alongside live event flows 
• Ensure pipeline reliability, throughput, and cost are actively managed at scale 

CI/CD & Deployment 

• Build and maintain CI/CD pipelines (GitHub Actions) across all portfolio products 
• Automate triage and retry logic for known failure classes — flaky tests, dependency timeouts, OOM kills — so engineers are only paged for genuinely novel failures 
• Deployment standards: release management, rollback mechanisms, canary and blue-green patterns where justified 

Observability & Reliability 

• Own the full observability stack: Grafana, Prometheus, and Loki across all products 
• SLOs and error budgets defined per product; reliability tracked consistently 
• Build alerting that correlates signals and surfaces diagnostic context alongside notifications — so on-call engineers arrive at an incident with hypotheses, not a blank screen 
• Incident response: on-call design, escalation playbooks, post-mortem facilitation 
• Automated remediation scoped to a defined set of safe, idempotent actions — container restarts, ECS task scaling, known rollback patterns. Novel or ambiguous failures escalate to a human with full context attached 

Acquisition Onboarding 

• Platform audit and gap analysis for every new acquisition — assessing CI/CD maturity, IaC coverage, observability gaps, and security posture 
• Migration plan and execution for each portfolio company joining the platform.
• Target: full platform integration within a defined window per acquisition 

What We're Looking For 

Experience & Background 

• 8–12 years in platform engineering, DevOps, or SRE — with clear evidence of increasing ownership over time 
• Strong Terraform depth across multi-environment, multi-account setups 
• CI/CD ownership across a multi-product environment with GitHub Actions 
• Experience with event streaming infrastructure at production scale — design, operations, reliability, and cost management 
• Hands-on Grafana, Prometheus, and Loki in production 
• AWS operational depth: ECS, EKS, RDS, IAM, VPC, CloudWatch, Cost Explorer 
• SRE fundamentals: SLOs, error budgets, on-call design, post-mortem culture 
• Acquisition or greenfield platform integration experience strongly preferred 

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

• Review, validate, and optimize existing Terraform code and AWS infrastructure.
• Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
• Design, build, and support secure, scalable, and highly available AWS environments.
• Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
• Lead infrastructure testing, performance tuning, and production readiness activities.
• Drive deployment and operationalization of the platform in the Production environment.
• Implement cloud governance, security, monitoring, and FinOps best practices.
• Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

• 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
• Proven experience designing, deploying, and managing AWS production environments.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience with CI/CD pipeline automation and DevOps practices.
• Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
• Experience in performance optimization, reliability, and cloud cost management (FinOps).
• Strong scripting and automation skills.
• Experience integrating enterprise applications through APIs and secure connectivity patterns.

We are looking for a hands-on Senior AWS Cloud Engineer to lead the infrastructure build, optimization, automation, and production deployment of a Multi-Agent AI Chatbot Platform hosted on AWS. The development environment is already in place, and the successful candidate will drive the solution through testing, integrations, and production go-live.

Key Responsibilities

• Review, validate, and optimize existing Terraform code and AWS infrastructure.
• Establish and manage integrations with enterprise platforms such as ServiceNow, Workday, and other third-party systems.
• Design, build, and support secure, scalable, and highly available AWS environments.
• Implement and automate CI/CD pipelines and Infrastructure-as-Code practices.
• Lead infrastructure testing, performance tuning, and production readiness activities.
• Drive deployment and operationalization of the platform in the Production environment.
• Implement cloud governance, security, monitoring, and FinOps best practices.
• Troubleshoot and resolve complex cloud infrastructure issues.

Required Skills & Experience

• 10+ years of IT experience with strong expertise in AWS Cloud Engineering.
• Proven experience designing, deploying, and managing AWS production environments.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience with CI/CD pipeline automation and DevOps practices.
• Expertise in AWS services including VPC, IAM, EC2, S3, Lambda, CloudWatch, and networking.
• Experience in performance optimization, reliability, and cloud cost management (FinOps).
• Strong scripting and automation skills.
• Experience integrating enterprise applications through APIs and secure connectivity patterns.

Preferred Skills

• Experience supporting AI/GenAI, chatbot, or multi-agent platforms.
• AWS Certifications (Associate/Professional).
• Banking or Financial Services domain experience.

This is a senior role in our Application & Database Modernization pillar, on a specific mission: leading a large-scale VMware-to-AWS migration and landing it in production. VMware estates are exactly where modernization programs go to stall — sprawling dependency graphs, undocumented workloads, and a hypervisor bill that grows while the migration deck gathers dust. Our customers need that estate moved, cut over, and retired, on a date in the contract.

You'll lead the design and implementation of the target infrastructure: Landing Zones built to AWS best practices, EKS-based container platforms, Infrastructure as Code across the stack with Terraform and CloudFormation, and HA, DR, security, and backup strategies that hold up in production. Aedeon absorbs the discovery, dependency-mapping, and validation grind that would otherwise consume the project's first two quarters. You own the judgment calls, architecture tradeoffs, cutover sequencing, risk decisions and you carry them through to production. You'll also mentor engineers and shape long-term infrastructure strategy with customer stakeholders. If you want your migration experience to end in retired VMware clusters rather than revised project plans, this is the role.

What you will do?

• Lead the design and implementation of infrastructure for a large-scale VMware-to-AWS migration — from discovery through production cutover.
• Architect and build secure, scalable, and highly available AWS environments, including Landing Zones that follow AWS best practices.
• Design and implement containerized application platforms on Amazon EKS; exposure to ECS is a plus.
• Implement Infrastructure as Code using Terraform and AWS CloudFormation.
• Define and enforce best practices across security, backups, high availability (HA), disaster recovery (DR), monitoring, and operations.
• Enable configuration management using tools such as Ansible, Chef, or similar.
• Build CI/CD pipelines and manage the complete build and release lifecycle for customer applications.
• Drive automation across provisioning, deployment, and operational workflows.
• Retire legacy infrastructure and land cloud-native architectures in its place.
• Improve and maintain DevOps platforms: Jenkins, Git repositories, monitoring, and observability stacks.
• Provide L3-level support for complex infrastructure and platform issues.
• Work with stakeholders on technical strategy and long-term architecture.
• Mentor engineers, contribute to talent evaluation, and support team development.

What are we looking for?

• 6+ years of hands-on DevOps experience, with strong expertise in designing and managing cloud infrastructure.
• Strong experience in VMware-to-AWS migration projects or large-scale infrastructure migrations.
• 4+ years of Terraform and CloudFormation for Infrastructure as Code (IaC).
• 4+ years in configuration management, systems engineering, and managing production-grade infrastructure.
• Solid Linux and/or Windows administration background.
• Deep understanding of AWS services, including VPC, EC2, IAM, EKS, ECS, RDS, S3, Backup, CloudWatch, etc.
• Experience with Kubernetes (EKS), ECS, and Docker in production environments.
• Hands-on experience designing HA, DR, security, and backup strategies.
• Experience with Landing Zone setup, multi-account strategy, and AWS governance frameworks.
• Proficiency in Git with a strong understanding of branching and merging strategies.
• Experience with CI/CD pipelines, automation, and operational tooling.
• A problem-solving mindset that's proactive and oriented toward reliability, performance, and scalability.

You will be preferred if

• Experience across multiple cloud platforms (AWS, Azure, GCP).
• AWS certifications such as Solutions Architect Associate/Professional or DevOps Engineer Professional.
• Exposure to data platforms such as Amazon EMR, Redshift, Lake Formation, and SageMaker.
• Experience designing cloud architectures at an L3/Architect level.

Job Title : Senior AWS DevSecOps & AI Platform Engineer

Experience Required : 5+ Years in AWS / Cloud Engineering

Terraform Experience : 4+ Years

Location : Gurugram

Work Mode : Onsite

Employment Type : Full-time

About the Role :

We are looking for an experienced Senior AWS DevSecOps & AI Platform Engineer with strong expertise in AWS cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD automation, cloud security, and database administration.

The ideal candidate will be responsible for designing and maintaining secure, scalable, reliable, and cost-efficient cloud environments while supporting microservices-based applications and implementing DevSecOps best practices. The role also involves building and deploying AI agents using Amazon Bedrock and Bedrock AgentCore, along with managing enterprise development and collaboration tools.

Mandatory Skills :

AWS (EC2, EKS, ECS, Lambda, S3, CloudWatch), Kubernetes, Terraform, Jenkins, Bitbucket Pipelines, CI/CD, DevSecOps, AWS Security Services (IAM, WAF, GuardDuty, Security Hub, KMS, Secrets Manager), Microservices, Helm, PostgreSQL, Oracle SQL, RDS, Jira, Confluence, Amazon Bedrock, Bedrock AgentCore, AWS Networking, and Cloud Cost Optimization.

Key Responsibilities :

• AWS Cloud Infrastructure : Design, implement, and maintain AWS infrastructure with a focus on scalability, availability, security, reliability, and cost optimization.
• Microservices & Containerization : Manage and support distributed microservices architectures, including deployment, monitoring, troubleshooting, performance optimization, service meshes, and API gateways.
• Kubernetes Administration : Administer and optimize Kubernetes clusters, including Amazon EKS and self-managed environments, covering upgrades, networking, workload management, scaling, and resource optimization.
• Cloud Security & Compliance : Implement and manage AWS security services, including IAM, GuardDuty, Security Hub, WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
• DevSecOps Implementation : Integrate security testing, vulnerability scanning, container security, and compliance-as-code tools into CI/CD pipelines.
• CI/CD & Source Control : Manage Bitbucket repositories, branching strategies, permissions, and Bitbucket Pipelines. Build and optimize Jenkins pipelines using declarative and scripted approaches.
• Infrastructure as Code : Develop and maintain Terraform modules, manage remote state and workspaces, detect infrastructure drift, and implement reusable infrastructure provisioning practices.
• Database Administration : Provision, manage, secure, and optimize AWS RDS databases, particularly PostgreSQL and Oracle, including backups, replication, patching, performance tuning, and migrations.
• Jira & Confluence Administration : Manage projects, workflows, automation rules, permissions, user access, spaces, schemes, and plugins.
• Monitoring & Reliability : Define and monitor SLIs, SLOs, and SLAs; implement observability best practices; and participate in incident management, root cause analysis, and post-incident reviews.
• AI Agent Development : Design, build, and deploy AI agents using Amazon Bedrock and Bedrock AgentCore, including agent runtime, memory, tools, gateway integration, identity and access management, guardrails, and lifecycle management across environments.
• Cloud Connectivity : Support hybrid cloud connectivity using AWS Direct Connect, VPN, and Transit Gateway.
• Cost Optimization : Apply FinOps practices to monitor cloud expenditure, optimize resource utilization, and improve infrastructure efficiency.
• API Integrations : Integrate third-party APIs while implementing authentication, rate limiting, error handling, and webhook management.

Required Skills & Qualifications :

• 5+ years of hands-on experience with AWS cloud services, including EC2, ECS, EKS, Lambda, ALB, CDN, S3, CloudWatch, Amazon Bedrock, and Bedrock AgentCore.
• Strong understanding of AWS networking, multi-account strategies, landing zone architecture, and hybrid connectivity.
• 4+ years of practical experience with Terraform, including module development, remote state management, workspaces, drift detection, and state operations.
• Extensive experience administering Kubernetes, preferably Amazon EKS, including Helm, Kustomize, operators, RBAC, network policies, autoscaling, and multi-tenancy.
• Proven experience managing distributed microservices, service meshes, API gateways, and inter-service communication.
• Strong knowledge of AWS security services, including IAM, Service Control Policies (SCPs), WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
• Experience implementing least-privilege access, zero-trust principles, and cloud security compliance controls.
• Hands-on experience integrating DevSecOps tools such as Snyk, Trivy, Checkov, and SonarQube into CI/CD pipelines.
• Understanding of OWASP security principles, CIS benchmarks, vulnerability management, and container security.
• Proficiency in Bitbucket repository administration, branch permissions, and YAML-based Bitbucket Pipelines.
• Strong experience developing and maintaining Jenkins CI/CD pipelines, shared libraries, plugins, and build agents.
• Experience administering AWS RDS databases, particularly PostgreSQL and Oracle SQL, including backup, replication, performance tuning, and migration activities.
• Experience administering Jira and Confluence, including workflows, permissions, automation, and plugin management.
• Working knowledge of Azure services, particularly Web Apps and Logic Apps/Workflows.
• Practical experience with Amazon Bedrock, including model invocation, guardrails, and AI agent development and deployment using Bedrock AgentCore.
• Understanding of third-party API integration, authentication mechanisms, rate limiting, error handling, and webhook management.
• Familiarity with FinOps practices and cloud cost optimization.

Good-to-Have Skills :

• Additional Azure experience, including networking, Azure SQL Managed Instance, and Azure Kubernetes Service (AKS).
• Hands-on experience with AI-driven Development Lifecycle (AI-DLC) methodologies and tools such as Kiro.

Relevant certifications, such as :

• AWS Certified Solutions Architect
• AWS Certified DevOps Engineer – Professional
• AWS Machine Learning or Generative AI certifications
• Certified Kubernetes Administrator (CKA)
• HashiCorp Terraform certifications

Ideal Candidate Profile :

The ideal candidate is a hands-on cloud and DevSecOps professional who can manage enterprise-scale AWS infrastructure, automate deployments, strengthen security controls, troubleshoot complex distributed systems, and support AI agent development. Strong problem-solving skills, an automation-first mindset, and the ability to collaborate across development, security, and infrastructure teams are essential.

 The Role 

As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that 

keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and 

observability that let a small, fast-moving team ship confidently — and you'll keep our AI and 

data workloads reliable and affordable at scale. 

This is a hands-on role with real ownership: you won't be maintaining someone else's setup, 

you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make 

deployment boring, incidents rare, and scaling a non-event. --- 

What You'll Own 

**CI/CD & developer experience** 

- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with 

confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible 

automated testing, rollbacks, and release controls. 

**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or 

similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. 

**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and 

resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch 

processing for the speech pipeline. 

**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, 

on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. 

**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and 

processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. 

**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in 

transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security 

requirements) for a product that handles sensitive customer conversations. 

**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability 

and spend. --- 

What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production 

systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and 

Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, 

Jenkins, Argo, or similar). 

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong 

automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, 

OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. 

Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch 

pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data 

pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud 

ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- 

Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real 

scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, 

and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an

Responsibilities:

• Add a new feature to existing infrastructure platforms.
• Collaborate across teams and lead technical discussions with clients and internal teams.
• Mentor junior team members through mob-pairing/1:1 pairing sessions.
• Adapt to different roles and technologies as project needs evolve.
• Proactive mindset with excellent client communication, collaboration, and writing skills.
• Use methodologies like Agile and Lean to manage projects and deliverables.
• Document technical solutions and knowledge for team reference.
• Stay current with industry trends and emerging technologies.

Requirements:

• Experience with managing large-scale infrastructure systems.
• Experience as a reliability engineer is good.
• Proficiency in at least one programming language.
• Good understanding of software delivery principles.
• Ability to adapt to different roles and technologies when needed

Required Technical Skills:

• You have spent some time building software systems or self-service systems for internal teams.
• You have a good understanding of Linux, software-defined, and cloud networking.
• You have work experience in configuration management and using tools like Ansible and Chef.
• You must have a good understanding of continuous integration and continuous delivery concepts, not just tools.
• Experience with tools like Jenkins, GitHub Actions, GitLab CI, etc. is required.
• It would be a plus if you have worked with GitOps tools like Argo CD or Flux CD.
• You are familiar with the cloud-native ecosystem and tools like Prometheus, OpenTelemetry, and Envoy.
• In-depth understanding of containers and container orchestrators like Nomad, Kubernetes, etc.
• You should deeply understand managing and organizing infrastructure as code and have worked with tools such as Terraform, Pulumi, CloudFormation, and AWS CDK.
• You are familiar with at least one primary cloud provider, such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure.
• You understand observability well and can collaborate with dev teams to improve their observability systems.
• You have a good understanding of the principles of distributed systems.
• You understand how SQL and NoSQL databases work and what is needed to manage them.
• You have familiarity with basic cloud security.

We're seeking an experienced Engineer to join our engineering team, handling massive-scale data processing and analytics infrastructure that supports over 1B daily events, 3M+ DAU, and 50k+ hours of content. The ideal candidate will bridge the gap between raw data collection and actionable insights, while supporting our ML initiatives.

Key Responsibilities

• Lead and scale the Infrastructure Pod, setting technical direction for data, platform, and DevOps initiatives.
• Architect and evolve our cloud infrastructure to support 1B+ daily events — ensuring reliability, scalability, and cost efficiency.
• Collaborate with Data Engineering and ML pods to build high-performance pipelines and real-time analytics systems.
• Define and implement SLOs, observability standards, and best practices for uptime, latency, and data reliability.
• Mentor and grow engineers, fostering a culture of technical excellence, ownership, and continuous learning.
• Partner with leadership on long-term architecture and scaling strategy — from infrastructure cost optimization to multi-region availability.
• Lead initiatives on infrastructure automation, deployment pipelines, and platform abstractions to improve developer velocity.
• Own security, compliance, and governance across infrastructure and data systems.

Who You Are

• Previously a Tech Co-founder / Founding Engineer / First Infra Hire who scaled a product from early MVP to significant user or data scale.
• 5–12 years of total experience, with at least 2+ years in leadership or team-building roles.
• Deep experience with cloud infrastructure (AWS/GCP), 
• Experience with containers (Docker, Kubernetes), and IaC tools (Terraform, Pulumi, or CDK).
• Hands-on expertise in data-intensive systems, streaming (Kafka, RabbitMQ, Spark Streaming), and distributed architecture design.
• Proven experience building scalable CI/CD pipelines, observability stacks (Prometheus, Grafana, ELK), and infrastructure for data and ML workloads.
• Comfortable being hands-on when needed — reviewing design docs, debugging issues, or optimizing infrastructure.
• Strong system design and problem-solving skills; understands trade-offs between speed, cost, and scalability.
• Passionate about building teams, not just systems — can recruit, mentor, and inspire engineers.

Preferred Skills

• Experience managing infra-heavy or data-focused teams.
• Familiarity with real-time streaming architectures.
• Exposure to ML infrastructure, data governance, or feature stores.
• Prior experience in the OTT / streaming / consumer platform domain is a plus.
• Contributions to open-source infra/data tools or strong engineering community presence.

What We Offer

• Opportunity to build and scale infrastructure from the ground up, with full ownership and autonomy.
• High-impact leadership role shaping our data and platform backbone.
• Competitive compensation + ESOPs.
• Continuous learning budget and certification support.
• A team that values velocity, clarity, and craftsmanship.

Success Metrics

• Reduction in infra cost per active user and event processed.
• Increase in developer velocity (faster pipeline deployments, reduced MTTR).
• High system availability and data reliability SLAs met.
• Successful rollout of infra automation and observability frameworks.
• Team growth, retention, and technical quality.

Role Overview

We are looking for a DevOps / Platform Engineer with 3–4 years of experience to help manage AWS cloud infrastructure, automation, and AI-ready platform operations. You will work closely with engineering and AI teams to ensure scalable, secure, and reliable deployments.

Key Responsibilities

1. AWS & Infrastructure: Manage core AWS services (EC2, EKS, Lambda, RDS, S3, VPC) using Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
2. AI/ML Workflows: Support infra for AI applications, model serving, vector databases, and GPU-based workloads.
3. CI/CD & Automation: Build and maintain deployment pipelines using GitHub Actions, GitLab CI, or Jenkins.
4. Containers & Kubernetes: Deploy and maintain containerized applications using Docker and Kubernetes (EKS) or ECS.
5. Observability & Incident Support: Maintain dashboards and alerts with CloudWatch, Prometheus, or Grafana, and participate in on-call response.
6. Security & FinOps: Apply AWS security best practices (IAM, encryption, secrets) and assist with cloud cost optimization.

Must-Have Skills & Qualifications

1. 3–4 years of experience in DevOps, SRE, or Cloud Infrastructure Engineering.
2. AWS & Containers: Good working knowledge of core AWS services, Docker, and Kubernetes (EKS).
3. Infrastructure-as-Code: Practical experience with Terraform, CloudFormation, or AWS CDK.
4. Linux & Networking: Solid fundamentals in Linux systems, DNS, routing, and load balancing.
5. Scripting: Hands-on scripting proficiency in Python, Bash, or Go.
6. CI/CD & Observability: Experience building CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) and using monitoring tools (CloudWatch, Prometheus, Grafana, or Datadog).

Nice-to-Have Skills

1. Basic exposure to AI/ML infrastructure, model serving, or GPU-based compute.
2. Experience with event-driven messaging systems (Kafka, Redis, or SQS).
3. Familiarity with GitOps tools and Helm (ArgoCD, Flux, or OpenTelemetry).
4. AWS Certifications (Solutions Architect Associate, SysOps Administrator, or DevOps Engineer).

Key Responsibilities

·       System Design: Design secure, scalable, and highly available multi-tenant cloud-based application architectures.

·       Integration Strategy: Build robust APIs, webhooks, and data pipelines for complex enterprise client connections.

·       Technical Guidance: Mentor software engineers and lead critical code and architecture reviews to ensure engineering excellence.

·       Performance & Security: Drive non-functional infrastructure needs including high uptime, strict data privacy compliance, and fast application response times.

·       Cross-Functional Collaboration: Partner closely with Product, Security, and Customer Success teams to align technical execution with business roadmaps.

Required Qualifications

·       Experience: 8+ years of experience in software engineering with at least 3+ years operating as a technical or solutions architect within a B2B SaaS environment.

·       Cloud & DevOps: Deep production knowledge of major cloud infrastructure (AWS, GCP, or Azure), containerization technologies (Docker, Kubernetes), and modern CI/CD automation pipelines.

·       Architecture Patterns: Proven expertise designing microservices, event-driven architectures, and high-performance relational and NoSQL database structures.

·       Communication: Strong written and verbal communication skills, with a proven ability to translate complex technical concepts clearly to both engineers and business stakeholders.

·       Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical work experience).

Preferred Skills

·        Prior experience managing architectural frameworks for enterprise compliance frameworks like SOC2, ISO 27001, or GDPR.

·        Background in building real-time data processing engines, stream frameworks, or integrating enterprise AI/ML components.