We are looking for a hands-on Infrastructure & Platform Engineer to build, operate and improve the cloud infrastructure and shared engineering capabilities used by our customer projects and internal teams. AWS is our primary cloud platform.

The role combines infrastructure and platform engineering, with a stronger emphasis on hands-on infrastructure. You will use infrastructure as code, automation and AI-assisted engineering workflows to deliver secure, reliable and cost-effective environments, troubleshoot operational and deployment issues, and create reusable platform capabilities that help development teams deliver software safely and independently.

The role suits an engineer who can work independently on well-defined outcomes, communicates clearly with technical and non-technical stakeholders, and is keen to learn unfamiliar services and systems.

Objective of the role

- Provision, change and maintain AWS infrastructure across development, test and production environments.
- Use Terraform as the primary infrastructure-as-code tool, while supporting AWS CDK-managed services where appropriate.
- Operate common AWS services covering networking, DNS, CDN and web hosting, identity and access, compute, storage, databases, messaging, secrets and monitoring.
- Maintain and improve CI/CD infrastructure, including GitHub Actions, deployment roles, OIDC integrations, secrets and environment configuration.
- Build and improve reusable platform capabilities, including Terraform modules, deployment patterns, guardrails, templates and self-service workflows for engineering teams.
- Investigate infrastructure, networking and deployment problems; identify root causes, implement safe fixes and verify outcomes.
- Apply practical security controls, including least-privilege IAM, secure secret handling, certificates, access controls and resource governance.
- Improve reliability and observability through useful logs, metrics, alerts, operational checks and runbooks.
- Participate in an out-of-hours on-call rota, responding to infrastructure alerts and incidents, carrying out initial diagnosis and remediation, and escalating or handing over when appropriate.
- Support infrastructure upgrades, capacity changes and cost optimisation.
- Create reusable automation and scripts that reduce manual work and make common changes repeatable.
- Use approved AI coding assistants and agents to accelerate investigation,



implementation, testing, documentation and pull-request preparation or review.
- Build safe, auditable AI-assisted workflows for repetitive operational work, with scoped access, appropriate human approval and clear evidence supporting any recommendation or change.
- Work directly with internal customers and project teams to clarify requirements, explain trade-offs and deliver pragmatic solutions.
- Keep technical documentation and handover notes accurate enough for another engineer to operate the service.

Essential Experience & Skills:

- Practical commercial experience building and operating infrastructure in AWS.
- Strong working knowledge of Terraform in production environments, including modules, state, plans and safe change management.
- Experience creating reusable infrastructure modules, deployment patterns, templates or other shared capabilities for engineering teams.
- Good understanding of Linux, command-line tooling and core networking concepts such as VPCs, subnets, routing, DNS, HTTP and TLS.
- Experience with CI/CD pipelines and source control; GitHub and GitHub Actions are preferred.
- Ability to automate routine tasks in at least one scripting language, such as Python, Bash, PowerShell or TypeScript.
- Practical experience using AI coding assistants or engineering agents in day-to-day work, together with the judgement to challenge, test and verify their output rather than accept it uncritically.
- Robust troubleshooting skills across infrastructure, application deployment and network boundaries.
- Willingness and ability to participate in the team's out-of-hours on-call rota.
- Awareness of cloud security fundamentals, especially IAM, secrets and least-privilege access.
- Ability to take ownership of work, prioritise sensibly and make progress with limited day-to-day supervision.
- Clear, customer-focused communication and a collaborative approach to supporting development teams.
- Curiosity and willingness to learn recent services, tools and project environments.





Desirable experience

- AWS CDK, particularly with TypeScript.
- Containers and Docker.
- Kubernetes or Amazon EKS, including Helm and cluster add-ons; deep platform-engineering expertise is not required.
- CloudFront, Route 53, WAF, API Gateway, Lambda, ECS, S3, DynamoDB, RDS, ElastiCache/Valkey or Amazon MQ.
- GitHub OIDC integrations and automated AWS deployments.
- Experience creating reusable AI instructions, prompts, skills or agent workflows for engineering and operational tasks.
- Familiarity with tool-connected AI workflows, such as Model Context Protocol (MCP) integrations for AWS, Terraform, Kubernetes, observability or engineering knowledge systems.
- Exposure to AI-assisted operations, such as telemetry investigation, alert enrichment, incident triage, knowledge retrieval or automated reporting.
- CloudWatch, New Relic, SigNoz or similar observability platforms.
- AWS cost analysis, rightsizing and practical FinOps improvements.
- Experience supporting multiple customer or product environments.
- Relevant AWS certification, although demonstrable hands-on experience is more important

What you’ll need to succeed: Within the first six months, the successful candidate should be able to:

- Deliver routine AWS and Terraform changes independently and safely diagnose and resolve common deployment, access, DNS, networking and service issues.
- Support project teams with clear advice and predictable follow-through.
- Improve a shared infrastructure or deployment capability that makes engineering teams more

self-sufficient.
- Use approved AI tools effectively while retaining ownership of technical decisions, validation and

security;
- Improve at least one recurring operational process through automation, an AI-assisted workflow

or better documentation; and contribute confidently to production changes, reviews and incident follow-up with appropriate support for higher-risk decisions. At Accedo, we are committed to fostering an environment of inclusiveness where employees are both valued and heard. Inclusion also means having diverse representation in gender, race, sex, thought, and other personal characteristics to contribute towards the betterment of our commerce and people. We strongly encourage applications from diverse communities to contribute towards our commitment of inclusivity.

📌 Infrastructure & Platform Engineer (Noida)
🏢 Accedo.tv
📍 Noida