Tower Lead (Support & Operations)

Technology, Data & Digital · Software & Web Development · Software Engineering · Cloud Engineering · Data Science

In short

We are seeking a Senior Forward Deployment Engineer (FDE) to lead the technical architecture and deployment of Generative AI and Agentic AI solutions on Google Cloud for strategic customers. This customer-facing role involves owning technical success, making architecture decisions, and leading FDEs.

Responsibilities

Own the overall technical delivery of enterprise Agentic AI deployments from discovery through production rollout and hypercare.
Lead customer discovery, technical workshops, architecture reviews, and executive technical discussions.
Design customer-specific AI and cloud architectures using Gemini Enterprise Agent Platform, ADK, and Google Cloud services.
Define agent architecture including multi-agent patterns, Planner/Critic/Supervisor/Orchestrator designs, domain agents, Skills, tools, RAG, human-in-the-loop controls, state, and enterprise integrations.
Define the integration architecture for REST APIs, MCP tools, databases, ITSM platforms, monitoring systems, identity systems, messaging systems, and proprietary applications.
Define production deployment architecture across Agent Runtime, Cloud Run, GKE, Cloud Functions, Pub/Sub, Cloud Storage, IAM, Secret Manager, networking, and other appropriate Google Cloud services.
Define production architecture requirements for availability, scalability, security, resiliency, observability, release management, rollback, disaster recovery, and operational support.
Lead security and identity architecture discussions covering IAM, RBAC, service accounts, authentication, authorization, secrets management, data protection, auditability, and network controls.
Define and review production readiness criteria covering functionality, security, performance, reliability, evaluation, observability, governance, supportability, and operational readiness.
Define the customer AgentOps strategy including telemetry, tracing, logging, metrics, evaluation, quality monitoring, cost monitoring, and operational dashboards.
Lead complex troubleshooting and root-cause analysis for production issues involving agents, models, RAG, tools, integrations, networking, authentication, and cloud infrastructure.
Drive reliability, latency, scalability, model performance, and AI cost optimization across customer deployments.
Define and review CI/CD, release management, environment promotion, versioning, rollback, and deployment processes.
Review architecture, integration code, deployment plans, and technical deliverables produced by FDEs; establish engineering quality standards.
Mentor and technically guide FDEs and Associate FDEs working on customer deployments.
Establish reusable deployment patterns, integration patterns, reference architectures, runbooks, onboarding standards, and troubleshooting playbooks.
Identify recurring customer requirements and drive their conversion into reusable agents, Skills, tools, connectors, frameworks, and platform capabilities with Agent Development / Platform Engineering teams.
Act as the senior technical escalation point for complex customer issues and major production incidents.
Provide technical feedback to Product, Agent Development, Platform Engineering, Security, Cloud Architecture, and Operations teams and influence platform roadmap priorities.
Lead technical handover, customer enablement, operational readiness, and transition to support/BAU teams.

Requirements

Strong Python and software engineering skills with the ability to review and guide production code.
Extensive hands-on experience with Generative AI, LLMs, RAG, prompt engineering, tool calling, evaluation, and multi-agent architectures.
Strong hands-on experience with ADK and/or LangGraph/LangChain in production.
Strong Google Cloud architecture and engineering experience with Gemini Enterprise Agent Platform / Google Cloud AI services.
Strong enterprise integration experience across REST APIs, databases, ITSM platforms, monitoring systems, identity platforms, and customer-specific applications.
Strong understanding of IAM, OAuth, service accounts, RBAC, secrets management, authentication, authorization, security, and enterprise networking.
Strong experience with containerized applications, Docker, Cloud Run, GKE, and production deployment patterns.
Strong experience with CI/CD, Git, release management, versioning, and production operations.
Strong experience with observability, tracing, logging, monitoring, debugging, evaluation, and production incident management.
Strong understanding of RAG architecture, knowledge integration, retrieval, evaluation, and agent quality measurement.
Experience with Responsible AI, guardrails, AI security, data protection, and enterprise governance.
Strong customer-facing communication skills and ability to lead architecture conversations with senior technical stakeholders.

Desired Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or related field.
8–12 years of overall software engineering, cloud engineering, solution architecture, or equivalent technical experience.
At least 3 years of practical Generative AI / Agentic AI experience.
Demonstrated track record of delivering multiple enterprise technology or AI solutions into production.
Demonstrated customer-facing technical leadership and architecture ownership.
Deep experience with Gemini Enterprise Agent Platform capabilities including ADK, Agent Runtime, Agent Gateway, Model Armor, Agent Evaluation, and Cloud Observability.
Experience with OpenTelemetry and enterprise AgentOps practices.
Experience with MCP, A2A, and enterprise agent interoperability.
Experience with Terraform / Infrastructure-as-Code and enterprise cloud landing zones.
Strong experience with GKE, Cloud Run, Pub/Sub, BigQuery, Cloud Storage, Secret Manager, networking, and private connectivity.
Experience with ServiceNow, ITSM, CloudOps, SRE, AIOps, infrastructure automation, or enterprise operations.
Experience designing highly available, scalable, secure production architectures.
Experience leading POCs, pilots, MVPs, production rollouts, and strategic enterprise deployments.
Exposure to multiple cloud platforms is advantageous.

Benefits

Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.

Skills

PythonGenerative AILLMsRAGPrompt EngineeringTool CallingAgentic AIGoogle CloudREST APIsDatabasesITSM platformsMonitoring systemsIdentity platformsIAMOAuthRBACDockerCloud RunGKECI/CDGitObservabilityLoggingMetricsCloud ObservabilityOpenTelemetryTerraformServiceNowSREAIOps

#GCP#Agentic AI#Generative AI#Solution Architecture#Production Strategy#Technical Governance#FDE Leadership#Customer Technical Leadership#Cloud

About HCLTech

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HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered around digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2022 totaled $12.1 billion. To learn how we can supercharge progress for…

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