Python developer

Strong Python Developer profile with robust AWS exposure

2

Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS

3

Mandatory (Tech skill 1): Must have strong working knowledge of Python.

4

Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR

5

Mandatory (Tech skill 3): Must be able to write and understand REST APIs

6

Mandatory (Tech skill 4): Experience designing and architecting scalable backend applications/services on AWS, including making decisions around application architecture, APIs, databases, and AWS services

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Mandatory (Tech skill 5): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab

8

Mandatory (Tech skill 6): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB

9

Mandatory (Tech skill 7): Must have familiarity with Linux commands and shell scripting

10

Mandatory (Skill 1): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance

11

Mandatory (Skill 2): Must have strong communication skills

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Preferred (Tech skill 2): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools

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Preferred (Tech skill 3): Basic understanding of CI/CD pipelines

14

Preferred (Tech skill 4): Experience with Docker or container-based applications

15

Preferred (Tech skill 5): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation

Strong Python Developer profile with robust AWS exposure

2

Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS

3

Mandatory (Tech skill 1): Must have strong working knowledge of Python.

4

Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR

5

Mandatory (Tech skill 3): Must be able to write and understand REST APIs

6

Mandatory (Tech skill 4): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab

7

Mandatory (Tech skill 5): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB

8

Mandatory (Tech skill 6): Must have familiarity with Linux commands and shell scripting

9

Mandatory (Skill): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance

10

Mandatory (Skill 2): Must have strong communication skills

11

Preferred (Tech skill 1): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools

12

Preferred (Tech skill 2): Basic understanding of CI/CD pipelines

13

Preferred (Tech skill 3): Experience with Docker or container-based applications

14

Preferred (Tech skill 4): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation

About the Role

We are looking for an experienced AWS DevOps Engineer with around 4 years of hands-on experience to join our infrastructure/DevOps team. The ideal candidate will independently design, deploy, and maintain cloud infrastructure primarily on AWS, drive automation initiatives, mentor junior engineers, and work closely with cross-functional teams to build scalable, secure, and highly available systems. Exposure to Azure is a strong plus.

Key Responsibilities

·      Design, deploy, and maintain robust, scalable, and secure infrastructure on AWS

·      Architect and manage core AWS services such as EC2, S3, VPC, IAM, RDS, Lambda, ECS/EKS, Route 53, and CloudFront

·      Build, own, and optimize CI/CD pipelines (e.g., CodePipeline, Jenkins, GitLab CI, GitHub Actions) to enable fast and reliable deployments

·      Design and implement Infrastructure as Code (IaC) using Terraform / AWS CloudFormation

·      Set up and manage monitoring, logging, and alerting solutions (CloudWatch, ELK, Prometheus, Grafana, Datadog, etc.)

·      Implement and enforce security best practices including IAM policies, security groups, NACLs, KMS, Secrets Manager, and compliance standards

·      Lead troubleshooting and root cause analysis for infrastructure, deployment, and production incidents

·      Drive backup, disaster recovery, high-availability, and cost-optimization strategies (Reserved Instances, Savings Plans, right-sizing)

·      Containerize applications and manage orchestration using Docker, ECS, and/or Kubernetes (EKS)

·      Automate repetitive operational tasks through scripting and tooling

·      Support any hybrid or multi-cloud initiatives involving Azure services, where applicable

·      Mentor junior engineers and review their work, providing technical guidance

·      Collaborate with development, QA, security, and product teams to support and streamline application deployments

·      Maintain comprehensive documentation of architecture, configurations, processes, and runbooks

·      Participate in on-call rotations and incident response as needed

Required Skills & Qualifications

·      Bachelor's degree in Computer Science, IT, or a related field (or equivalent practical experience)

·      4+ years of hands-on experience working with AWS cloud services in a production environment

·      Strong expertise in core AWS services: EC2, S3, VPC, IAM, RDS, Lambda, CloudWatch, ECS/EKS, Route 53, ELB/ALB, Auto Scaling

·      Solid understanding of networking concepts (subnets, routing, security groups, load balancers, VPNs, VPC peering, Direct Connect)

·      Strong scripting/programming skills in Python, Bash, or PowerShell for automation

·      Hands-on experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation

·      Proven experience with Linux and/or Windows server administration

·      Strong understanding of CI/CD pipelines, Git-based version control, and branching strategies

·      Solid experience with containerization and orchestration (Docker, ECS, or EKS/Kubernetes)

·      Experience with configuration management tools (Ansible, Chef, or Puppet) is a plus

·      Application Server Management — strong knowledge of networking, firewalls, load balancers, Nginx, Apache, etc.

·      Ability to independently read, interpret AWS documentation, and troubleshoot complex issues

·      Experience with cost optimization, security audits, and compliance frameworks (e.g., ISO, SOC2) is a plus

·      AWS certification (Solutions Architect Associate/Professional, DevOps Engineer Professional) preferred

Good to Have

·      Working knowledge of Microsoft Azure services (Virtual Machines, VNets, Azure DevOps, Azure Storage, Azure AD/Entra ID, AKS)

·      Experience with multi-cloud or hybrid-cloud environments

·      Familiarity with Azure Resource Manager (ARM) templates or Bicep

·      Any Azure certification (AZ-104, AZ-400, etc.)

Soft Skills

·      Strong analytical, problem-solving, and decision-making ability

·      Excellent verbal and written communication skills

·      Ability to mentor and guide junior team members

·      Proactive, ownership-driven approach to infrastructure and incident management

·      Strong collaboration skills in a cross-functional, team-oriented environment

·      High attention to detail with a focus on reliability and scalability

Data Engineer

Location: Bengaluru, India (Hybrid)

Employment Type: Full-time

Experience: 3-5 years

Role Overview  

What We’re Looking For:

• Bachelor’s degree in Computer Science/Engineering or equivalent experience required.
• Experience designing and shipping cloud services products.
• Experience driving and managing technical and architectural dependencies on AWS Cloud.
• A firm understanding of system architecture, cloud computing, PaaS/SaaS design principles, S3, DynamoDB, RDS mandatory.
• Experience in building or maintaining ETL processes and tools, i.e., AWS Glue or any open-source tool.
• Proven system-level design contribution to a current “Live” (in production / under daily high load) multi-region SaaS or PaaS offering.
• Proven experience with S3, DynamoDB, SQL, and AWS RDS services.
• Proficiency in programming languages such as Python.
• Strong analytical and problem-solving skills.
• 
  

Required Skills & Experience

• Experience with Python, SQL, and data visualization/exploration tools.
• Familiarity with the AWS ecosystem, specifically S3, DynamoDB, and RDS.
• Communication skills, especially for explaining technical concepts to nontechnical business leaders.
• Ability to work on a dynamic, research-oriented team that has concurrent projects.
• Experience in AWS cost optimization (Savings Plans, Reserved Instances, Spot Instances) and governance frameworks.
• Experience developing solutions using infrastructure orchestration tools (SSM, automation account, Ansible, etc.).
• Excellent leadership, stakeholder management, and communication skills.

What We Offer

• Work with some of the brightest minds in the emerging EV industry.
• Make a tangible impact in reducing carbon emissions and enabling sustainable energy.
• Freedom to suggest, implement, and innovate on systems, processes, and technologies.
• Daily ownership in a high-growth, challenging environment.
• Flexible work environment with hybrid schedules and virtualization options.
• Competitive pay and benefits including health coverage, innovative PTO program, and performance bonuses.

Job Summary

We are looking for an experienced AWS Cloud Engineer with strong expertise in AWS infrastructure, deployment, migration, and cloud operations. The candidate should have hands-on experience managing AWS services such as EC2, EBS, S3, EFS, and FSx, along with infrastructure provisioning, migration, troubleshooting, and optimization.

Key Responsibilities

• Design, deploy, configure, and manage AWS infrastructure environments.
• Perform application and infrastructure migration to AWS.
• Provision and manage EC2 instances, including configuration, scaling, patching, and troubleshooting.
• Manage EBS volumes, snapshots, backups, and storage performance.
• Configure and administer S3 buckets, storage policies, lifecycle management, and access controls.
• Manage EFS for scalable shared file storage.
• Implement and manage Amazon FSx file systems based on application requirements.
• Monitor AWS infrastructure performance, availability, and capacity.
• Troubleshoot infrastructure, networking, storage, and deployment-related issues.
• Implement security best practices including IAM, security groups, encryption, and access controls.
• Support backup, disaster recovery, high availability, and business continuity requirements.
• Optimize AWS resources for performance, scalability, reliability, and cost.

Mandatory Skills

• Strong hands-on experience in AWS Cloud Infrastructure.
• Expertise in EC2, EBS, S3, EFS, and FSx.
• Experience in AWS deployment and migration projects.
• Strong knowledge of AWS networking concepts such as VPC, Subnets, Route Tables, Security Groups, and Load Balancers.
• Experience with IAM and AWS security best practices.
• Good knowledge of AWS monitoring and troubleshooting.
• Experience with cloud infrastructure automation using Terraform or CloudFormation is preferred.
• Strong Linux administration and troubleshooting skills.
• Good understanding of backup, disaster recovery, and high-availability concepts

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

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)

• Linux troubleshooting
• Hands-on AWS
• Production/Application Support
• Bash/Shell/Python
• Monitoring/log analysis
• Incident resolution
• Application deployment/support
• Basic networking and database knowledge
• Production/batch support exposure
• Willingness for rotational weekend/critical production support

Forward-deployed engineers (FDEs) are Mactores' services layer. You embed with the customer's team, own outcomes from discovery through the production cutover, and personally carry the delivery commitment.

The agent platform we deploy absorbs 60–70% of engagement work, discovery, assessment, design, and testing. You absorb the judgment: target architecture, refactoring trade-offs, model selection, cutover strategy, and the decisions an agent platform cannot make. The agent absorbs scale. You absorb judgment. 

This is not a staff-augmentation seat and not an advisory role. You ship.

What you will do?

• Deliver production agentic AI systems and AWS modernization engagements on committed dates across three pillars: Data Platform Modernization, Application & Database Modernization, and AI Agents for Apps.
• Build and productionize AI agents, orchestration, retrieval pipelines, evaluation harnesses, observability running against real customer data, not demo data.
• Convert existing products into agents: expose product functionality as callable tools for agent-to-agent composition, or replace form-and-click UX with agent-native, intent-driven interfaces.
• Convert existing Business processes into agents: expose process functionality as callable tools for agent-to-agent composition, or replace form-and-click UX with agent-native, intent-driven interfaces.
• Embed directly with customer engineering teams. Run architecture sessions, defend design decisions, and align stakeholders from VP Engineering to CTO.
• Make agent decisions traceable and defensible, validation runs in parallel with live workloads, and outputs hold up to internal audit and regulators (HIPAA, PCI-DSS, FSI-grade governance where the vertical demands it).
• Feed field experience back into the platform and practice: your deployment patterns, integration playbooks, and edge cases shape how we deliver.

What are we looking for?

• Excellent communication skills (English) — verbal and written. Non-negotiable. You will present architecture to customer CTOs, write documents that hold up in audit, and defend judgment calls in the room. If you can build but not explain, this role is not a fit.
• You have shipped production agentic AI systems on AWS. Not POCs, not notebooks — systems running in production for real users. This is the primary qualification. Be prepared to walk through what you shipped, the decisions you made, and what broke.
• Deep understanding of agentic architecture — you can design an agent system from first principles and explain why each component exists:
• Agent design patterns: single-agent vs. multi-agent systems, supervisor/orchestrator patterns, hierarchical agent topologies, planner–executor separation, and when each applies.
• Orchestration: building and operating orchestrator agents that decompose tasks, route work to specialist agents or tools, and manage state across multi-step workflows (LangGraph, Strands Agents, CrewAI, or equivalent).
• Memory: short-term/working memory (context management, conversation state) and long-term memory (episodic and semantic stores, vector- and graph-backed retrieval), and the production trade-offs of each.
• Reflection and self-correction: critique loops, self-evaluation, retry-with-feedback patterns, and evaluation harnesses that catch agent failures before customers do.
• Tool use and function calling: schema design, tool-selection reliability, error handling, and agent-to-agent composition.
• RAG and retrieval pipelines: chunking, embedding, hybrid retrieval, reranking, and grounding agent decisions in customer data.
• Strong AWS production experience: Amazon Bedrock and AWS AI services, plus core platform services (Lambda, API Gateway, DynamoDB, RDS/Aurora, Glue, EMR, Redshift, Kinesis, or similar depending on specialization).
• Solid software engineering fundamentals Python, TypeScript, CI/CD, infrastructure-as-code, testing-driven development discipline.
• Experience with data or application modernization (database migration, legacy refactoring, data platform builds) is a strong plus, since agents run against these workloads.
• Indicative experience: roughly 3–10 years in engineering roles, with agentic AI / GenAI as your current day job. We have demonstrated agent-native expertise over tenure — an engineer with 3–4 years of hands-on agentic AI work typically outperforms a 12-year generalist on this work.

You'll be preferred if you've:

• US English verbal and written fluency 
• Delivery experience in one or more of our verticals: Financial Services, Healthcare & Life Sciences, Internet & Software, Manufacturing, or Telco/Media/Entertainment/Gaming/Sports.
• Model tuning and fine-tuning: systematic prompt engineering and optimization; parameter-efficient fine-tuning (LoRA/QLoRA or similar); instruction tuning; working knowledge of RLHF/DPO; sound judgment on when to fine-tune vs. prompt vs. RAG; and evaluation of tuned models against baselines. Fine-tuning experience on Amazon Bedrock or SageMaker is a plus.
• Experience with compliance-sensitive AI systems (HIPAA, PCI-DSS, SOC 2, data residency).
• Knowledge graph, code-analysis (AST), or CDC/streaming experience (Debezium, Kafka/MSK).
• Solid software engineering fundamentals — Java, C++, Go Lang, .Net, Rust
• Prior customer-facing consulting or forward-deployed experience.
• AWS certifications (Solutions Architect Professional, Machine Learning Specialty, or Data Analytics).

Why This Role?

• You own outcomes, not tickets. FDEs carry the delivery commitment personally — architecture, judgment, and cutover are yours.
• You work agent-native from day one. Our delivery model would not function without agents. You build with the platform, not around it.
• You ship. Engagements measured in weeks to production, legacy retired, outcomes named. No archived pilots.
• You compound. Field delivery informs the Aedeon platform roadmap; the platform's growth expands what you can deliver. Few engineering roles sit in that loop.

Mactores is the agent-native AWS modernization firm. Most modernization work doesn't ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores' founders' sister company, which absorbs the repetitive 60–70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.

Legacy infrastructure doesn't retire itself. Someone has to build the pipelines, rehearse the cutover, and carry the release into production  and that's this seat. As a Senior AWS DevOps Engineer, you serve our application and infrastructure modernization work: you own build and release cycles for customer projects, land migrations from legacy hardware to AWS, and make deployments boring in the best sense of the word.

Agents change what this job looks like day to day. Aedeon and automation handle the repetitive discovery, mapping, and validation work that used to eat engineer hours. That leaves you the parts that actually need a senior engineer: infrastructure architecture, risk tradeoffs, release judgment, and the operational standards the whole team ships against. You'll work client-facing, embedded with customer teams, and the delivery commitment is one you carry personally.

What we are looking for?

• 4+ years with Terraform for Infrastructure as Code (IaC) including modules, remote state, state management, imports and multi account providers.
• Experience in designing highly available and secure AWS architecture within strong understanding of RTO/RPO and DR Strategies.
• 4+ years in configuration management and systems engineering, supporting large-scale Agile environments.
• 4+ years of Linux or Windows administration.
• 4+ years working with Git, with a solid grasp of branching and merging strategies.
• 4+ years hands-on with AWS infrastructure and platform services.
• 2+ years with cloud automation tools such as Ansible or Chef.
• 2+ years with container orchestration, Kubernetes (EKS), AWS ECS, and Docker.
• A proactive, solutions-oriented approach and a drive to improve reliability and scalability.

What you will do?

• Automate infrastructure creation with Terraform and AWS CloudFormation — infrastructure as code, not tickets and toil.
• Own application configuration management and drive Infrastructure as Code through deployment tooling.
• Own the build and release cycle for customer projects, end to end.
• Share responsibility for deploying releases and for operations and maintenance work.
• Improve the operations infrastructure we ship with — Jenkins clusters, Bitbucket, monitoring tools (Consul), and metrics tools like Graphite and Grafana.
• Support the engineering team operationally and help migrate legacy infrastructure to the cloud — retiring the old systems, not just standing up new ones.
• Establish and enforce operational best practices, and hold releases to them.
• Help hire culturally aligned engineers and mentor them as they grow.
• Work with the founders on team strategy and long-term technical planning.
• Work across distributed teams in the US and India, and with customer SMEs, to keep the business logic honest through migration.