Technical Specialist

Technology, Data & Digital · Data, AI & Analytics · Artificial Intelligence · Software Engineering

In short

This role focuses on designing, developing, and deploying production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise. Key responsibilities include integrating with Google Workspace, architecting memory and state management, implementing robust security protocols, and leveraging developer tooling for rapid prototyping and deployment in client environments.

Responsibilities

Design, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise.
Identify the need for Pro Code vs. No Code design based on customer requirements and data.
Design, deploy, and customize agents using the Agent Development Kit (ADK) and Agent Platform AI Reasoning Engine, integrating with Gemini Enterprise.
Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for enterprise research and document automation.
Architect scalable session storage, conversation state persistence, and long-term memory architectures for multi-agent interactions.
Implement end-to-end authentication and authorization for agents, Google Cloud services, and 3rd-party SaaS integrations.
Enforce fine-grained Access Control Lists (ACLs), user/group permission inheritance, and data governance policies.
Utilize developer tooling like Agent CLI and Antigravity for rapid prototyping, testing, and root cause analysis (RCA).
Architect Human-in-the-Loop (HITL) workflows with seamless interrupt and resume patterns.
Build and maintain automated CI/CD pipelines for agent deployments, testing, and regression evaluations.
Implement advanced reasoning patterns like Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection.
Establish quantitative evaluation frameworks to measure agent performance and reasoning faithfulness.
Collaborate with client engineering and architecture teams to deploy and operationalize enterprise agentic AI solutions.

Requirements

Strong proficiency in Python with production-level software engineering practices.
Deep, hands-on experience building multi-agent systems using Google ADK or comparable agentic frameworks.
Solid hands-on experience deploying and customizing Gemini Enterprise, NotebookLM, and integrating with the Google Workspace Ecosystem.
Demonstrated expertise in managing agent session state, short-term context caching, and durable long-term memory backends.
Experience with MCP Connectors to securely integrate third-party platforms (e.g., iManage, NetDocuments, Relativity, DocuSign, MS Office Suite, Sharepoint, JIRA) with Gemini Enterprise.
Strong understanding of authentication and authorization protocols (IAM, OAuth 2.0, OIDC, Service Accounts, Workload Identity Federation) across Google Cloud and 3rd-party SaaS platforms.
Deep working knowledge of enterprise Access Control Lists (ACLs), identity federation, permission trimming, and role-based access control (RBAC).
Proficiency in developer tooling such as Agent CLI and Antigravity.
Proven track record of configuring and maintaining automated CI/CD pipelines (Cloud Build, GitHub Actions) for agent containerization, deployment, and test automation.
Practical knowledge of AI evaluation methodologies, trajectory analysis, and performing root cause analysis (RCA).
Strong technical communication, consulting acumen, and client-facing collaboration skills within an Agile environment.

Desired Qualifications

Experience in software development, cloud solution architecture, and AI engineering (preferably on Google Cloud Platform).
Proven track record of designing, building, and deploying production AI agents or enterprise GenAI solutions using ADK, Vertex AI, or Gemini.
Hands-on experience in customer-facing technical delivery, solutions engineering, or forward-deployed engineering (FDE) roles.
Familiarity with enterprise Agile development lifecycles, sprint delivery, and stakeholder management.
Experience with inter-agent communication protocols such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) architectures.
Experience integrating agents with Enterprise Knowledge Graphs, structured ontologies, and hybrid vector search systems.
Experience with enterprise data security frameworks such as Sensitive Data Protection (SDP/DLP) and VPC Service Controls (VPC-SC).
Professional Machine Learning Engineer certification.
Google Skill Boost labs/courses related to Gemini Enterprise and ADK.

Benefits

Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.
Global technology company with over 223,000 people across 60 countries.
Industry-leading capabilities centered around digital, engineering, cloud and AI.
Work with clients across all major verticals, including Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services.

Skills

PythonMulti-Agent SystemsGemini EnterpriseAgent Development Kit (ADK)Google WorkspaceNotebookLMIAMOAuth 2.0OIDCMicrosoft Entra IDSalesforceAtlassianAccess Control Lists (ACLs)Agent CLIAntigravityCloud BuildGitHub ActionsGitLab CIChain-of-Thought (CoT)ReActPlan-and-SolveSelf-ReflectionVector DatabasesiManageNetDocumentsRelativityDocuSignMS Office SuiteSharepointJIRARole-Based Access Control (RBAC)Sensitive Data Protection (SDP/DLP)VPC Service Controls (VPC-SC)Vertex AI

#AI#Machine Learning#Software Development#Cloud#Google Cloud

About HCLTech

Supercharging progress through technology and innovation

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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