Forward Deployed Engineer

Project Role : Forward Deployed Engineer

Project Role Description : Organize the deployment of AI workflows and architectures across diverse AI and technology platforms. Facilitate solution design across enterprise technology stack to integrate into the ecosystem of AI models and multi provider platforms.

Must have skills : Amazon Web Services (AWS)

Good to have skills : NA

Minimum 12 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

A Principal Engineer Cloud leads the hands-on design, build, and operation of large-scale cloud infrastructure across AWS and GCP. The role is accountable for engineering secure, resilient, and cost-optimized cloud platforms building real infrastructure, writing real code, and owning outcomes end to end alongside product, security, and application engineering teams.

This individual operates as a recognized cloud engineering authority setting platform standards, driving infrastructure automation, and solving complex distributed cloud Infrastructure challenges including having good understanding of the insurance industry. In a financial services context, engineering decisions must satisfy stringent regulatory requirements including PCI DSS, SOX, and DORA, alongside enterprise-grade reliability and availability commitments.

Roles & Responsibilities:

Cloud Platform Engineering

Design, build, and operate large-scale, cloud-native infrastructure across AWS and GCP owning platform reliability, security posture, and cost efficiency

Implement and maintain infrastructure-as-code across both cloud platforms using Terraform and native tooling enforcing standards, modularity, and drift detection

Build and maintain CI/CD pipelines, GitOps workflows, and deployment automation for cloud infrastructure and platform services

Engineer landing zones, account vending, and governance guardrails on AWS (Control Tower, SCPs) and GCP (Resource Manager, Org Policies)

AI Orchestration: High Level understanding of LangChain, LlamaIndex, CrewAI agentic workflow design, multi-agent orchestration, tool calling, human-in-the-loop workflows

Design and implement cloud networking AWS VPC, Transit Gateway, Direct Connect and GCP VPC, Shared VPC, Cloud Interconnect for hybrid and multi-cloud connectivity

Implement security controls across IAM, network policy, encryption, secrets management, and audit logging on both platforms

Drive platform observability metrics, logging, distributed tracing, and alerting using CloudWatch, GCP Operations Suite, and third-party tooling

Perform capacity planning, cost analysis, and right-sizing to maintain efficient cloud spend across AWS and GCP estates

LLM & AI Tooling: High Level Understanding of OpenAI, Anthropic Claude, Google Gemini prompt engineering, RAG architecture, vector databases (Pinecone, Weaviate, ChromaDB), LLMOps

Application & Container Platform Engineering

Engineer and operate Kubernetes-based container platforms EKS on AWS and GKE on GCP including cluster lifecycle, node management, networking, and security hardening

Define and enforce standards for microservices, APIs, event-driven architectures, and data platform integrations across cloud environments

Collaborate with application engineering teams on cloud-native design patterns serverless, service mesh, and distributed data stores Build and maintain developer platform tooling internal developer portals, self-service infrastructure, and platform APIs to accelerate engineering delivery

Drive observability and reliability engineering practices SLIs, SLOs, error budgets, and chaos engineering across cloud-hosted services

Support secure software delivery SAST, DAST, container image scanning, and supply chain security in CI/CD pipelines

Technical Leadership & Engineering Excellence

Set cloud engineering standards, patterns, and reference architectures codified in reusable Terraform modules, runbooks, and design guides

Lead proof-of-concept and spike work for emerging cloud technologies making build-vs-buy recommendations grounded in engineering evidence

Conduct technical design reviews and production readiness assessments for cloud-hosted services

Mentor senior and mid-level engineers providing hands-on guidance on IaC, cloud-native patterns, and production operations

Drive continuous improvement of the cloud platform reducing toil through automation, improving reliability, and eliminating technical debt

Contribute engineering patterns and reusable modules back to internal platform teams and cloud centre of excellence

Professional & Technical Skills:

Must-Have Technical Skills

Infrastructure as Code: Terraform (advanced) modular design, remote state, workspace strategy, and policy-as-code (Sentinel/OPA) across AWS and GCP

Containers & Kubernetes: EKS and GKE cluster lifecycle, CNI, RBAC, admission controllers, network policies, and production-grade operations

Cloud Networking: Deep expertise in hybrid connectivity, multi-cloud routing, DNS strategy, and network security across both platforms

Security Engineering: IAM design, zero-trust principles, encryption at rest/in transit, secrets management (Vault, AWS Secrets Manager, GCP Secret Manager), and CSPM

CI/CD & Automation: GitHub Actions, ArgoCD, Terraform Cloud, or equivalent GitOps workflows, pipeline security, and infrastructure deployment automation

AI Orchestration: High Level Understanding of LangChain, LlamaIndex, CrewAI agentic workflow design, multi-agent orchestration, tool calling, human-in-the-loop workflows

Observability: Metrics, logging, and distributed tracing at scale SLO engineering, alerting design, and incident response tooling

Scripting & Development: Python or Go automation scripting, SDK usage for AWS and GCP, and platform tooling development

LLM & AI Tooling: High Level understanding of OpenAI, Anthropic Claude, Google Gemini prompt engineering, RAG architecture, vector databases (Pinecone, Weaviate, ChromaDB), LLMOps

Incident Management: Production incident ownership, structured RCA, and reliability engineering practices in high-availability FSI environments

Cost Engineering: FinOps practices reserved instance/committed use optimisation, tagging strategy, and cost allocation across AWS and GCP estates

Preferred / Advantageous

Experience with service mesh (Istio or Linkerd) for microservices networking and observability

Familiarity with data platform engineering Kafka, Spark, or cloud-native analytics services on AWS or GCP

Exposure to FinOps tooling CloudHealth, Apptio Cloudability, or native cloud cost management platforms

Background in platform engineering, SRE, or cloud infrastructure consulting within financial services

Additional Information:

Certifications

• AWS Solutions Architect
  
  

Professional GCP Professional Cloud Architect AWS DevOps Engineer

Professional or GCP DevOps Engineer

Cloud platforms on AWS and GCP are secure, observable, and reliably operated meeting FSI SLA and regulatory requirements consistently

Infrastructure-as-code coverage is comprehensive environments are reproducible, drift-free, and deployable through automated pipelines without manual intervention

Engineering teams across the organisation adopt platform standards, reusable modules, and cloud-native patterns reducing bespoke build effort and improving consistency Platform reliability improves measurably quarter-on-quarter MTTR reduces, toil decreases, and error budgets are maintained across cloud-hosted services

Cross-functional stakeholders security, application, data, and operations teams regard the Principal Engineer as a technically authoritative, delivery-focused partner who unblocks rather than bottlenecks

• The candidate should have minimum 12 years of experience in Amazon Web Services (AWS).
• This position is based at our Bengaluru office.
• A 15 years full time education is required.