Project Role : Full Stack Engineer
Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset.
Must have skills : Docker Kubernetes Architecture
Good to have skills : Infrastructure As Code (IaC), Ansible on Microsoft Azure, Cloud Automation DevOps
Minimum
7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
AI Powered Tech Talent
We are looking for a Senior Full Stack Platform Engineer with 8+ years of experience to lead enterprise platform engineering strategy and architecture. You will define golden paths, drive platform adoption, and enable developer productivity through internal developer platforms, automation, and secure-by-design practices. This is a leadership role requiring both technical depth and cross-functional influence.
You will shape the platform engineering vision, define standards, ensure resilience, security, and cost efficiency, and guide modernization journeys for global clients.
You will also be responsible for capability development initiatives, writing Points of View (POVs), white papers, and developing new assets.
Roles & Responsibilities:
Define and implement enterprise-wide platform strategy across cloud, DevOps, Kubernetes, IaC, AI-enabled workflows, and application
deployment.
Architect secure, scalable cloud landing zones with integrated CI/CD, observability, compliance automation, and cost optimization.
Establish governance frameworks, policy-as-code, and security guardrails for multi-cloud and hybrid platforms.
Lead the design of internal developer platforms (IDP), golden paths, and reusable service catalogs.
Mentor and guide platform engineering teams, driving adoption of best practices and modern patterns (GitOps, DevSecOps, SRE).
Integrate advanced deployment strategies (blue-green, canary, chaos engineering, automated rollback).
Collaborate with enterprise architects, security teams, and application teams to ensure alignment with business goals.
Evangelize platform engineering principles across the organization via communities of practice.
Evaluate and integrate AI/ML and GenAI capabilities into CI/CD, observability pipelines, cloud operations, and security workflows.
Lead integration of AI services such as AWS Bedrock, Azure OpenAI, Google Vertex AI into secure landing zones.
Architect AI-powered platform automation including:
- Intelligent code generation, IaC reviews, and policy validation
- AI-driven anomaly detection, incident triage, drift detection
- automated insights for cost optimization, capacity planning, and performance tuning
Implement Agentic Automation using multi-agent systems for:
- Self-healing infrastructure
- Auto-remediation workflows
- Compliance and security guardrail enforcement
- Cost & performance optimization
Guide teams on LLM adoption patterns, embeddings, vector databases, inference optimization, and integration of AI features into platform services.
Build strategy and standards for:
- AI governance, responsible AI, model evaluation frameworks
- prompt engineering, prompt orchestration, retrieval-augmented generation (RAG)
- secure AI deployment on enterprise-grade infrastructure
Bring an architectural perspective to the full AI lifecycle: data readiness, model selection, evaluation, deployment, monitoring, and value realization.
Professional & Technical Skills:
Proven expertise in multi-cloud architecture (AWS, Azure).
Deep hands-on experience with Kubernetes (multi-cluster, service mesh, operators/CRDs) and GitOps-based delivery.
Mastery of IaC architecture and policy-as-code (Terraform Enterprise, Crossplane, OPA, Sentinel, Pulumi, Ansible).
Ability to design enterprise DevOps platforms (self-service CI/CD, observability, governance, security scanning).
Strong architectural vision across infrastructure, security, databases, and application delivery.
Ability to write and orchestrate deployment scripts (Bash, PowerShell, Ansible, Python).
Integrate Enterprise Observability & Reliability solutions (Prometheus, Grafana, ELK, Splunk, New Relic, SRE practices)
Demonstrated ability to lead cross-functional platform transformations.
Cost & Governance: FinOps, optimization frameworks, governance automation
Exceptional communication, collaboration, and leadership skills.
GenAI & Emerging Technologies:
Generative AI (Core)
Strong understanding of LLMs, embeddings, vector databases, prompt engineering, RAG architectures.
Hands-on experience integrating cloud-based GenAI (Bedrock, Azure OpenAI, Vertex AI).
Ability to drive AI project delivery: discovery solution design prototyping deployment.
Agentic AI
Experience with multi-agent frameworks for self-healing infrastructure, cost automation, and enforcement of security guardrails.
Understanding of planning, task decomposition, autonomy, and AI-driven decision workflows.
AI/ML Fundamentals
Solid foundation in machine learning concepts: supervised & unsupervised learning, model evaluation, data analysis, and statistical reasoning.
Knowledge of neural networks, transformers, embeddings, and NLP fundamentals. Executive certifications:
Cloud Professional Certification (Any 2)
- AWS: Solutions Architect Professional, DevOps Professional
- Azure: Solutions Architect Expert, DevOps Engineer Expert
DevOps Professional (Any One)
- AWS: DevOps Professional
- Azure: DevOps Engineer Expert
Terraform (Any One): HashiCorp Certified: Terraform Associate
Kubernetes (Any 2): Certified Kubernetes Administrator, Certified Kubernetes Application Developer, Certified Kubernetes Security Specialist (CKS)
Additional Information:
- The candidate should have minimum 7.5 years of experience in Docker Kubernetes Architecture and Design.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
- Resource needs to be AI Ready.
