Note: Need Immediate Joiners.

Forward Deployed Engineer, Platform & AI

Level: Senior / Staff (8–12 years)

About the role

We help enterprises ship software faster and operate it more safely through a self-service internal developer platform, an AI-powered operations layer, and customer-facing applications. You will work directly with customers to understand their environment (clouds, ITSM, security and compliance constraints), then design, build and deploy solutions that work in production.

This is a hands-on engineering role. You’ll write code, run infrastructure, and sit in the room with the customer’s platform, security and operations teams.

What you’ll do

- Embed with customers to understand their delivery, operations and compliance pain points, and turn them into scoped, shippable solutions.
- Design and build platform capabilities: golden paths and blueprints, self-service workflows, multi-tenant isolation, and shared services.
- Build secure delivery pipelines: IaC, CI/CD, GitOps, and security scanning (SAST, DAST, vulnerability and secret scanning) shifted left.
- Build and integrate CMDB, policy-based alerting, patch management and compliance workflows, connected to ITSM tools (incident, problem, change, release).
- Build AI-powered capabilities: LLM agents, retrieval (RAG), memory and context management, guardrails and evaluation, grounded in operational data.
- Build clean, rapid customer-facing web applications and APIs on top of the platform.
- Make systems observable and reliable: metrics, events, logs and traces (MELT), SLOs, and on-call-ready runbooks.
- Document, demo and hand over, so customers can run what you build.
- Feed learnings back to the core product team so one-off solutions become reusable features.

What you’ll bring: must-haves




- Systems and platform engineering: strong Kubernetes and Linux skills, plus hands-on experience with at least one major cloud (AWS, Azure, GCP or OCI).
- System design: data modeling and storage choices (relational, NoSQL, vector, graph), caching, rate limiting, networking, security fundamentals, and distributed-systems trade-offs (consistency, consensus, failure modes).
- DevSecOps: Git-based workflows, Infrastructure as Code (Terraform/OpenTofu or equivalent), CI/CD (Argo Workflows, GitHub Actions or similar), GitOps (ArgoCD or Flux), and security scanning in the pipeline.
- Platform mindset: you have built or run golden paths, self-service tooling or multi-tenant platforms, and care about developer experience.
- AI in production: practical experience shipping LLM-based features, including RAG, tool use or agents, evaluation, and guardrails.
- Full-stack ability: comfortable building a modern web frontend (e.g., React/TypeScript) and backend APIs (e.g., Python).
- Customer-facing communication: you can run discovery, explain trade-offs to technical and non-technical people, and say no with reasons.

Strong plus

- Enterprise ITSM process knowledge (incident, problem, change, release) and tools such as ServiceNow or Jira Service Management.
- CMDB and asset-discovery experience.
- Policy-based compliance, patch management or alert-governance experience.
- Graph or semantic modeling of operational data (knowledge graphs, a “semantic layer” over CMDB or telemetry).
- Agent frameworks, memory and context-engineering experience, and LLM evaluation harnesses.
- FinOps awareness and cost-conscious design.
- Experience in regulated industries (finance, healthcare, public sector).
- Cloud or Kubernetes certifications (CKA/CKS, AWS/Azure/GCP professional).

Note: Need Immediate Joiners.

📌 Forward Deployed Engineer, Platform & AI (India)
🏢 ValueLabs
📍 India