About the Role & Your Career
Fast-Track: Are you a hands-on Google Cloud Professional-certified Engineer who wants to step up into an elite Agentic AI Forward Deployment Engineer (FDE)? HCLTech is hiring high-potential Senior Google Cloud & GenAI Engineers in the US and India to join our accelerated FDE Launchpad Cohort within our Strategic Google AI Transformation Practice.
You do NOT need prior experience as a Forward Deployment Engineer—we are looking for strong Python and Google Cloud builders who already hold an active Google Cloud Professional Certification and have the drive to master enterprise multi-agent AI.
When you join, you will enter our sponsored 60-Day Fast-Track FDE Launchpad Program, where HCLTech will train, mentor, and sponsor you through dual Google Cloud Partner Specialist (CPS) credentials and Google's exclusive in-person Elite FDE Bootcamp.
Upon graduating from the program, you will be badged and deployed as a Certified Forward Deployment Engineer (FDE) into high-impact Google Cloud Professional Services (PSO) customer engagements.
How Your Journey Works (What You Will Do)
Phase 1 — First 60 Days: Sponsored FDE Launchpad & CoE Apprenticeship (25%)
Complete the sponsored Fast-Track FDE Certification Pathway within your first 60 days:
Pass 2x Google Partner Specialist Challenge Labs (Gemini Enterprise Deployment & Agent Development).
Graduate from Google's exclusive 4-Day (32-Hour) In-Person Elite FDE Bootcamp.
Apprentice directly alongside our US and India AI Capability Center (CoE) Leads and Elite AI Guild—learning advanced multi-agent orchestration (Google ADK 2.0, A2A protocols, MCP servers), enterprise AI security (SPIFFE, Model Armor, VPC-SC), and LLM evaluation harnesses while contributing to our Reusable AI Asset Factory.
Phase 2 — Post-Graduation: Operating as a Certified Google Cloud FDE (75%)
Co-Build in Agile Customer Sprints (50%): Embed directly within Google Cloud PSO customer engineering pods across US and APAC engagements (6–8 week co-build sprints) to rapidly architect, code, and deploy production multi-agent AI systems.
Agentic Engineering & Integrations: Build end-to-end agentic workflows using Google Agent Development Kit (ADK), Vertex AI Agent Engine, Gemini Enterprise, Model Context Protocol (MCP) integration servers, Agent-to-Agent (A2A) protocols, and REST/gRPC microservices.
Data Grounding, Security & EvalOps (25%): Ground enterprise agents using Vertex AI Search, BigQuery, AlloyDB, Spanner, and Enterprise Knowledge Graphs (EKG); enforce production security (VPC-SC, Workload Identity Federation, Cloud KMS, Cloud DLP De-identification, Model Armor) and automated LLM-as-a-judge evaluation suites.
Required Qualifications (What You Must Bring on Day 1)
- Active Google Cloud Professional Certification (MANDATORY): You must currently hold at least ONE active, verifiable Google Cloud Professional Certification:
- Professional Cloud Architect
- Professional Data Engineer
- Professional Machine Learning Engineer
- Professional Cloud Developer / DevOps Engineer / Security Engineer
- 5–10+ years of hands-on software engineering, cloud engineering, or data/AI engineering experience, with at least 1.5–2+ years building Generative AI, LLM, RAG, or agentic applications in Python.
- Strong production coding proficiency in Python (and/or TypeScript/Go), SQL, REST/gRPC APIs, and containerized cloud runtimes (Cloud Run, GKE, Docker, Terraform).
- Hands-on experience with core Google Cloud AI, Data & Security services—such as Vertex AI, Gemini APIs, Vertex AI Search, BigQuery, AlloyDB, Cloud Storage, and IAM / VPC-SC.
- Practical experience with at least one modern LLM or agent orchestration framework (e.g., LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or Google ADK / Vertex AI Agent Builder).
- High-Velocity "Builder-Consultant" Mindset: Strong communication skills, intellectual curiosity, and eagerness to work directly with client engineers to turn ambiguous business problems into working production code.
Preferred / Bonus Qualifications (Nice to Have)
- Exposure to LLM evaluation techniques (golden datasets, autoraters), prompt guardrails/DLP, or Knowledge Graphs.
- Prior project experience in any key enterprise industry vertical (such as Financial Services, Healthcare & Life Sciences, Retail/eCommerce, Telecom/Media, or SaaS/ISVs).