11+ Innovation management Jobs in India

This is a full-time on-site role for a Technical Project Head with Project leadership & Agile Expertise. They will be responsible for the day-to-day management of projects, ensuring that timelines are met, budgets are adhered to, and communication with stakeholders is maintained. Project Leadership: Lead and manage cross-functional teams to ensure successful development & execution & define the overall architecture and technical direction for development projects Technical Expertise: Demonstrate a deep understanding & Oversee the backend services, databases, and third-party API integration & frontend technologies/tools. And best practices to effectively guide with budgeting & providing technical support to the development team along with assisting them in making architectural decisions. Task Assignment: Define project tasks, allocate resources, and delegate responsibilities to team members while considering their strengths and expertise & assessing the feasibility of cross-platform development, and deciding when to adopt it based on project requirements. Timelines and Milestones: Develop and communicate project timelines, milestones, and deliverables, ensuring alignment with expectations and company objectives. Risk Management: Identify potential project risks, devise mitigation strategies, and proactively address issues to keep the project on track while at the same time ensuring industry-standard security practices, authentication mechanisms, data encryption, and compliance with relevant privacy regulations. Status Updates: Regularly collect updates from team members, track project progress, and provide transparent status reports to stakeholders. Problem Solving: Swiftly addresses technical challenges, conflicts, and roadblocks, making data-driven decisions to ensure project momentum. Quality Assurance: Implement quality control measures to guarantee that the final product aligns with the project scope, technical standards, and requirements. Deadline Adherence: Employ effective time management strategies to meet project deadlines and exceed expectations. Documentation: Prepare the technical documentation, flow, and execution plan of the project including specifications & architecture. Qualifications: Bachelor's degree in Computer Science, Information Technology, or a related field (Master's preferred). Proven experience (5+ years) as a Senior IT Project Manager leading similar successful responsibilities mentioned above. Proficiency in frontend technologies such as HTML, CSS, JavaScript, and related frameworks. Strong knowledge of backend technologies such as databases (SQL, NoSQL), server-side scripting (PHP, Node.js, Python, etc.), API integrations & development. Solid understanding of project management methodologies (Agile, Scrum, etc.). Excellent leadership, interpersonal, and team-building & management skills. 

Job Title : Mobile DevOps Engineer

Experience : 5+ Years

Location : Nashik / Pune (Remote – Initial 1 Week Onsite in Nashik)

Job Summary :

We are looking for a Mobile DevOps Engineer with expertise in building and maintaining CI/CD pipelines for iOS and Android applications. The ideal candidate will have hands-on experience with mobile build automation, release management, Azure DevOps, and cloud-based DevOps practices to enable faster, secure, and reliable mobile application delivery.

Mandatory Skills :

Azure DevOps, Mobile CI/CD (iOS & Android), Fastlane/Bitrise/Codemagic, GitHub, Xcode, Gradle, App Store & Google Play release automation, YAML Pipelines, GitHub Actions, Docker, Shell/Python scripting, Mobile DevSecOps, Firebase Crashlytics/Sentry, Agile/Scrum.

Key Responsibilities :

• Design, implement, and maintain CI/CD pipelines for iOS and Android applications.
• Automate build, testing, code signing, and deployment processes.
• Manage app releases on Google Play Store and Apple App Store.
• Configure and maintain Azure DevOps pipelines, GitHub workflows, and release automation.
• Integrate automated testing, security scanning, and quality gates into CI/CD pipelines.
• Monitor build performance, troubleshoot pipeline issues, and optimize release processes.
• Collaborate with Mobile, QA, Backend, and Product teams to streamline delivery.
• Maintain DevOps documentation, release procedures, and deployment best practices.
• Explore AI-powered development tools to improve automation and developer productivity.

Required Skills :

• 5+ years of experience in DevOps, Infrastructure, or Software Engineering.
• 2+ years of hands-on experience with Mobile CI/CD (iOS & Android).
• Strong experience with Azure DevOps, GitHub, Fastlane, Bitrise, Codemagic, or similar tools.
• Solid knowledge of Xcode, Gradle, code signing, provisioning profiles, and keystores.
• Experience with Google Play Store and Apple App Store release automation.
• Familiarity with YAML pipelines, GitHub Actions, Shell/Python scripting, and Docker.
• Knowledge of mobile testing frameworks, DevSecOps practices, and monitoring tools such as Firebase Crashlytics, Sentry, or Datadog.
• Understanding of Agile/Scrum methodologies and strong collaboration skills.

Preferred Skills :

• Experience with Flutter, React Native, or native mobile development.
• Exposure to Azure Cloud services.
• Familiarity with AI-assisted development tools and automation.

About the Role

We are looking for passionate and driven interns across multiple technology domains including Frontend Development, Backend Development, DevOps, AI/ML, and Data Engineering. This internship offers hands-on experience in real-world projects, collaboration with cross-functional teams, and exposure to modern tools and technologies. 

Domains & Responsibilities 

Frontend Development 

• Build responsive and user-friendly web interfaces  
• Translate UI/UX designs into functional applications  
• Optimize performance and ensure cross-browser compatibility  

 Backend Development 

• Develop APIs and server-side logic  
• Work with databases and data storage solutions  
• Ensure application security and performance  

 DevOps 

• Assist in CI/CD pipeline setup and automation  
• Manage deployments and cloud infrastructure  
• Monitor system performance and reliability  

 AI / Machine Learning 

• Develop and train ML models  
• Work on NLP, automation, or AI-driven features  
• Analyze datasets and evaluate model performance  

 Data Engineering 

• Build and maintain data pipelines (ETL/ELT)  
• Ensure data quality and availability  
• Work with large datasets and optimize data workflows  

 Required Skills (Any Domain) 

• Frontend: HTML, CSS, JavaScript, React/Vue/Angular  
• Backend: Node.js / Python / Java / PHP, APIs, databases  
• DevOps: Linux, Git, CI/CD basics, cloud fundamentals  
• AI/ML: Python, ML basics, TensorFlow/PyTorch/Scikit-learn  
• Data Engineering: SQL, Python, data processing concepts  

 Good to Have 

• Knowledge of Git and version control  
• Basic understanding of cloud platforms (AWS/Azure/GCP)  
• Problem-solving mindset and willingness to learn  
• Exposure to real-world or academic projects  

 Who Should Apply 

• Students or recent graduates in Computer Science, IT, or related fields  
• Candidates with strong interest in any of the above domains  
• Self-learners with project experience are highly encouraged  

 Internship Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO (Pre-Placement Offer) based on performance  

 What You’ll Gain 

• Hands-on experience with real projects  
• Mentorship from experienced professionals  
• Exposure to industry tools and workflows  
• Opportunity to convert to a full-time role 

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)

Review Criteria

• Strong DevOps /Cloud Engineer Profiles
• Must have 3+ years of experience as a DevOps / Cloud Engineer
• Must have strong expertise in cloud platforms – AWS / Azure / GCP (any one or more)
• Must have strong hands-on experience in Linux administration and system management
• Must have hands-on experience with containerization and orchestration tools such as Docker and Kubernetes
• Must have experience in building and optimizing CI/CD pipelines using tools like GitHub Actions, GitLab CI, or Jenkins
• Must have hands-on experience with Infrastructure-as-Code tools such as Terraform, Ansible, or CloudFormation
• Must be proficient in scripting languages such as Python or Bash for automation
• Must have experience with monitoring and alerting tools like Prometheus, Grafana, ELK, or CloudWatch
• Top tier Product-based company (B2B Enterprise SaaS preferred)

Preferred

• Experience in multi-tenant SaaS infrastructure scaling.
• Exposure to AI/ML pipeline deployments or iPaaS / reverse ETL connectors.

Role & Responsibilities

We are seeking a DevOps Engineer to design, build, and maintain scalable, secure, and resilient infrastructure for our SaaS platform and AI-driven products. The role will focus on cloud infrastructure, CI/CD pipelines, container orchestration, monitoring, and security automation, enabling rapid and reliable software delivery.

Key Responsibilities:

• Design, implement, and manage cloud-native infrastructure (AWS/Azure/GCP).
• Build and optimize CI/CD pipelines to support rapid release cycles.
• Manage containerization & orchestration (Docker, Kubernetes).
• Own infrastructure-as-code (Terraform, Ansible, CloudFormation).
• Set up and maintain monitoring & alerting frameworks (Prometheus, Grafana, ELK, etc.).
• Drive cloud security automation (IAM, SSL, secrets management).
• Partner with engineering teams to embed DevOps into SDLC.
• Troubleshoot production issues and drive incident response.
• Support multi-tenant SaaS scaling strategies.

Ideal Candidate

• 3–6 years' experience as DevOps/Cloud Engineer in SaaS or enterprise environments.
• Strong expertise in AWS, Azure, or GCP.
• Strong expertise in LINUX Administration.
• Hands-on with Kubernetes, Docker, CI/CD tools (GitHub Actions, GitLab, Jenkins).
• Proficient in Terraform/Ansible/CloudFormation.
• Strong scripting skills (Python, Bash).
• Experience with monitoring stacks (Prometheus, Grafana, ELK, CloudWatch).
• Strong grasp of cloud security best practices.

Why this role exists

Our infrastructure footprint is growing faster than our headcount, and we believe most of that

gap should be closed by automation and AI agents — not by hiring more humans to do toil. We

need someone early in their career who treats manual work as a bug, ships scripts and agents

instead of tickets, and wants to grow into deeper ownership over the next two years.

You will not be the most senior person on the team. You will be the one who multiplies the team.

What you'll own

In your first 1 months

• Take ownership of one slice of our CI/CD pipeline and make it measurably

faster, more reliable, or cheaper. We expect a number on a dashboard to move.

• Build at least three internal automations that replace manual ops toil —

using AI agents (Claude Code, agentic CLIs, scripted LLM workflows) as your force

multiplier.

• Be the first responder for a defined set of alerts. Write the runbooks. Drive

the alert volume down.

• Support senior engineers on AI/ML infrastructure (GPU nodes, inference

services, model deployment) — observe, document, and gradually take on contained

changes under review.

By 3 months you should be

• The go-to person for at least two production systems.

• Shipping routine infrastructure changes without needing senior review.

• Treating "manual" as a code smell.

Required (we will reject without these)

• 0–3 years hands-on experience with one major cloud (AWS, GCP, or

Azure — one is fine, depth beats breadth).

• Fluent in Linux command line, bash, and at least one scripting language

(Python or Go preferred).

• Have shipped something to production that real users hit. A side project

counts; a graded coursework lab does not.

• Comfortable with Docker — you can explain what an image vs. a

container is and why it matters.

• Working knowledge of networking fundamentals: DNS, HTTP/HTTPS,

TLS, ports, basic subnets — enough to debug "it works on my machine."

• Git fluency: branches, merges, rebases, conflict resolution.

• CI/CD pipelines — you have authored or substantially modified pipelines

in GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar. Not just "I clicked Re-run."

• Kubernetes basics — kubectl for real work, can read pod logs,

understand deployments and services, can debug a CrashLoopBackOff without

panicking. You do not need to have run a cluster; you do need to have lived inside one.

• Active user of AI coding agents (Claude Code, Cursor, Copilot, agentic

CLIs, etc.). You should be able to walk us through specific tasks where they made you

faster, and specific tasks where they failed you and how you noticed. "I have tried it" is

not enough.

Bonus (real plus, not required)

• Infrastructure as Code: Terraform, Pulumi, or Ansible.

• Observability: Prometheus/Grafana, Datadog, OpenTelemetry, any APM.

• Have built or extended an LLM-based agent — a custom MCP server, a

scripted multi-step workflow, an internal tool that calls models in a loop. Anything beyond

chat-with-Claude.

• Exposure to GPU workloads, model serving (vLLM, Triton, TGI, etc.), or

ML pipelines.

What we don't care about

• Whether your degree is in CS — or whether you have a degree at all.

• Brand-name companies on your resume.

• Certifications. They are fine. They do not substitute for having shipped.

How we work

• We default to automation. If you do something manually twice, the third

time you script it or hand it to an agent.

• AI agents are part of the workflow, not a novelty. Expect interview

questions about exactly how you use them — and where you have caught them being

wrong.

• Small, reversible changes beat big-bang rollouts.

• Postmortems are blameless and written down.

• We push back on each other. If you only execute, you will be unhappy

here.

How to apply

Send:

• Your resume.

• A short note (≤200 words) describing one infra or automation problem you

solved, and how AI agents factored in — or did not, and why. We read these. Generic

notes get rejected.

Internal note — delete before posting externally

• Comp band, location policy, team name, and reporting line marked

[CONFIRM] need to be filled in before this goes external.

• The Required list is intentionally tight: CI/CD and Kubernetes basics

promoted from bonus. Expect this to filter ~80% of typical junior DevOps applicants. The

remaining pool will skew toward people who have actually shipped infra at a startup, not

bootcamp grads or pure cloud-cert holders.

• IaC, observability, agent-building, and GPU/ML serving stay as bonus.

Promoting any of these to required at 0–3 yrs collapses the pool to near-zero or forces

hiring senior people at junior comp. If you want IaC required, re-level this to mid (3–5

yrs) and raise the band.

• Screening implication: the resume screen should explicitly check for

CI/CD pipeline authorship and any K8s-touching production work. If neither is on the

resume, reject at screen. Do not waste interview slots.

• Pipeline watch: if fewer than ~15 qualified resumes after 2 weeks of

active sourcing, the first thing to relax is the AI-agent-fluency bar (move to bonus and

screen for it in interview instead). Do not relax the "shipped to production" requirement

— that is the load-bearing filter.

As part of the Cloud Platform / Devops team at Upswing, you will get to work on building state-of-the-art infrastructure for the future. You will also be –

• Building Infrastructure on AWS driven through terraform and building automation tools for deployment, infrastructure management, and observability stack 
• Building and Scaling on Kubernetes
• Ensuring the Security of Upswing Cloud Infra
• Building Security Checks and automation to improve overall security posture 
• Building automation stack for components like JVM-based applications, Apache Pulsar, MongoDB, PostgreSQL, Reporting Infra, etc.
• Mentoring people across the teams to enable best practices 
• Mentoring and guiding team members to upskill and helm them develop work class Fintech Infrastructure

What will you do if you join us?

• Write a lot of code
• Engage in a lot of cross-team collaboration to independently drive forward infrastructure initiatives and Devops practices across the org 
• Taking Ownership of existing, ongoing, and future initiatives 
• Plan Architecture- for upcoming infrastructure
• Build for Scale, Resiliency & Security 
• Introduce best practices wrt Devops & Cloud in the team
• Mentor new/junior team members and eventually build your own team

You should have

• Curiosity for on-the-job learning and experimenting with new technologies and ideas
• A strong background in Linux environment
• Must have Programming skills and Experience
• Strong experience in Cloud technologies, Security and Networking concepts, Multi-cloud environments, etc.
• Experience with at least one scripting language (GoLang/Python/Ruby/Groovy)
• Experience in Terraform is highly desirable but not mandatory
• Experience with Kubernetes and Docker is required 
• Understanding of the Java Technologies and Stack
• Any other Devops related experience will be considered

Role:

• Developing a good understanding of the solutions which Company delivers, and how these link to Company’s overall strategy.
• Making suggestions towards shaping the strategy for a feature and engineering design.
• Managing own workload and usually delivering unsupervised. Accountable for their own workstream or the work of a small team.  
• Understanding Engineering priorities and is able to focus on these, helping others to remain focussed too
• Acting as the Lead Engineer on a project. Helps ensure others follow Company processes, such as release and version control.
• An active member of the team, through useful contributions to projects and in team meetings.
• Supervising others. Deputising for a Lead and/or support them with tasks. Mentoring new joiners/interns and Masters students. Sharing knowledge and learnings with the team.

Requirements:

• Acquired strong proven professional programming experience.
• Strong command of Algorithms, Data structures, Design patterns, and Product Architectural Design.
• Good understanding of DevOps, Cloud technologies, CI/CD, Serverless and Docker, preferable AWS 
• Proven track record and expert in one of the field - DevOps/Frontend/Backend
• Excellent coding and debugging skills in any language with command on any one programming paradigm, preferred Javascript/Python/Go
• Experience with at least one of the Database systems - RDBMS and NoSQL
• Ability to document requirements and specifications.
• A naturally inquisitive and problem-solving mindset.
• Strong experience in using AGILE or SCRUM techniques to build quality software.
• Advantage: experience in React js, AWS, Nodejs, Golang, Apache Spark, ETL tool, data integration system, certification in AWS, worked in a Product company and involved in making it from scratch, Good communication skills, open-source contributions, proven competitive coding pro