Forward Deployed Engineer

Overview

Organize the deployment of AI workflows and architectures across diverse AI and technology platforms. Facilitate solution design across the enterprise technology stack to integrate with AI models and multi-provider platforms.

What you'll do

• Design, build, and operate enterprise observability platforms using Splunk, providing unified metrics, logging, and tracing across infrastructure tiers with OpenTelemetry instrumentation standards.
• Engineer and govern the infrastructure-as-code platform using Terraform or Pulumi, including module libraries, state management, policy-as-code, drift detection, and multi-cloud coverage across AWS and GCP.
• Build and maintain CI/CD and GitOps pipeline infrastructure using GitHub Actions and ArgoCD for infrastructure and application platform delivery.
• Operate the Internal Developer Portal, Backstage, for self-service provisioning.
• Own ITSM platform engineering, including ServiceNow workflow automation, CMDB reconciliation, PagerDuty/OpsGenie integrations, and automated incident creation pipelines across infrastructure towers.
• Engineer LLM-powered runbook automation integrating OpenAI, Anthropic Claude, or Google Gemini with infrastructure tooling to automate incident triage, resolution workflows, and knowledge base queries.
• Build agentic ITSM workflows using multi-agent orchestration to handle incident classification, runbook execution, and stakeholder communication with human-in-the-loop controls.
• Implement AI-powered alert correlation and noise reduction to group related alerts, suppress false positives, and surface actionable incident context to on-call engineers.
• Design RAG architectures for infrastructure knowledge bases backed by vector databases.
• Engineer secret management infrastructure using HashiCorp Vault, including dynamic secrets, PKI automation, and Kubernetes authentication across multi-cloud and on-premises environments.
• Mentor engineers across infrastructure towers, set platform engineering standards, drive tooling roadmaps, and act as the highest technical escalation point for platform and AI tooling issues.

What you'll need

• Minimum 7.5 years of experience in Agentic Orchestration.
• 15+ years in platform, tools, or infrastructure engineering.
• 15 years of full-time education.
• Mandatory certifications: Terraform Associate or Professional, Splunk Professional, AWS DevOps Engineer Pro or GCP DevOps Engineer, Certified Kubernetes Administrator (CKA), and HashiCorp Vault Associate.
• Experience with Splunk SLO engineering, OpenTelemetry, ELK/Splunk log pipelines, and distributed tracing.
• Experience with advanced Terraform modular design, policy-as-code, drift detection, and Ansible/Chef for configuration management.
• Experience with GitHub Actions, ArgoCD pipeline engineering, GitOps workflows, policy enforcement, and infrastructure deployment automation.
• Experience with ServiceNow workflow automation, CMDB integration, incident/problem/change API integration, and PagerDuty/OpsGenie connectivity.
• Experience with service catalogues, golden path templates, self-service provisioning, and plugin development for an Internal Developer Portal.
• Experience with HashiCorp Vault dynamic secrets, PKI automation, Kubernetes authentication, and multi-cloud secrets lifecycle.
• Experience with OpenAI, Anthropic Claude, or Google Gemini prompt engineering, RAG architecture, vector databases, and LLMOps.
• Experience with LangChain, LlamaIndex, or CrewAI agentic workflow design, multi-agent orchestration, tool calling, and human-in-the-loop workflows.
• Advanced Python experience for platform tooling development, LLM SDK integration, infrastructure automation, and API development.
• Experience with PCI DSS, SOX, and DORA platform access controls, audit logging, policy-as-code enforcement, and regulatory evidence production.

Nice to have

• Experience with Crossplane for Kubernetes-native cloud resource provisioning.
• Experience with eBPF-based observability, including Cilium, Pixie, or Hubble for deep infrastructure telemetry.
• Experience with AI/ML infrastructure, GPU node management, model serving platforms such as Triton or vLLM, or MLflow.
• Platform engineering or SRE consulting background within financial services.

Details

• Based at the Bengaluru office.