Senior Technical Lead

Job description

Design, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise ● Identify need for Pro Code Vs No Code design based on customer’s problem statement and data sources ● Design Deploy and custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise ● Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery. ● Architect scalable short-term session storage, conversation state persistence, and long-term memory architectures across multi-agent interactions. ● Implement end-to-end authentication and authorization perimeters for agents, Google Cloud services, and 3rd-party SaaS integrations (e.g., Microsoft Entra ID / M365, Salesforce, Atlassian) using IAM, OAuth 2.0, OIDC, and service identities. ● Enforce fine-grained Access Control Lists (ACLs), user/group permission inheritance, and data governance policies to ensure agents strictly adhere to enterprise access boundaries. ● Utilize developer tooling including Agent CLI and Antigravity for local rapid prototyping, testing, emulation, distributed tracing, and root cause analysis (RCA). ● Build and maintain automated CI/CD pipelines (e.g., Cloud Build, GitHub Actions, GitLab CI) to manage versioned agent deployments, automated testing, and continuous regression evaluations. ● Implement advanced reasoning patterns such as Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection to enhance agent reliability. ● Establish quantitative evaluation frameworks to measure agent trajectories, tool invocation precision/recall, and reasoning faithfulness. Key Responsibilities Design, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise ● Identify need for Pro Code Vs No Code design based on customer’s problem statement and data sources ● Design Deploy and custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise ● Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery. ● Architect scalable short-term session storage, conversation state persistence, and long-term memory architectures across multi-agent interactions. ● Implement end-to-end authentication and authorization perimeters for agents, Google Cloud services, and 3rd-party SaaS integrations (e.g., Microsoft Entra ID / M365, Salesforce, Atlassian) using IAM, OAuth 2.0, OIDC, and service identities. ● Enforce fine-grained Access Control Lists (ACLs), user/group permission inheritance, and data governance policies to ensure agents strictly adhere to enterprise access boundaries. ● Utilize developer tooling including Agent CLI and Antigravity for local rapid prototyping, testing, emulation, distributed tracing, and root cause analysis (RCA). ● Build and maintain automated CI/CD pipelines (e.g., Cloud Build, GitHub Actions, GitLab CI) to manage versioned agent deployments, automated testing, and continuous regression evaluations. ● Implement advanced reasoning patterns such as Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection to enhance agent reliability. ● Establish quantitative evaluation frameworks to measure agent trajectories, tool invocation precision/recall, and reasoning faithfulness. Skill Requirements Must-Have Skills ● Core Engineering & Frameworks: Strong proficiency in Python with production-level software engineering practices, along with deep, hands-on experience building multi-agent systems using Google ADK (Agent Development Kit) or comparable agentic frameworks. ● Gemini & Workspace Ecosystem: Solid hands-on experience deploying and customizing Gemini Enterprise, NotebookLM, and integrating with the broader Google Workspace Ecosystem (APIs, Add-ons, Drive/Docs connectors). ● Memory & State Architecture: Demonstrated expertise in managing agent session state, short-term context caching, and durable long-term memory backends (vector databases, relational/NoSQL session stores). ● Third Party Tools: Experience with MCP Connectors to securely integrate core third-party platforms (e.g., iManage, NetDocuments, Relativity, DocuSign, MS Office Suite, Sharepoint, JIRA) with Gemini Enterprise. ● Auth & Security: 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 (Microsoft Entra ID, Salesforce, Atlassian). ● ACLs & Permissions: Deep working knowledge of enterprise Access Control Lists (ACLs), identity federation, permission trimming, and role-based access control (RBAC) across heterogeneous data sources. ● Developer Tooling: Proficiency in developer tooling such as Agent CLI and Antigravity for local simulation, debugging, prompt engineering, and execution graph tracing. ● CI/CD & DevOps: Proven track record of configuring and maintaining automated CI/CD pipelines (Cloud Build, GitHub Actions) for agent containerization, deployment, and test automation. ● Evaluation & Debugging: Practical knowledge of AI evaluation methodologies, trajectory analysis, and performing root cause analysis (RCA) on agent execution failures, tool errors, and prompt regressions. ● Client Collaboration: Strong technical communication, consulting acumen, and client-facing collaboration skills within an Agile environment. Good-to-Have Skills ● 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). Qualifications and Prior Experience ● 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. Other Requirements Certifications and Trainings ● Professional Machine Learning Engineer ● Google Skill Boost labs/course ○ Introduction to Gemini Enterprise : https://partner.skills.google/course_templates/1401 ○ Gemini Enterprise and NotebookLM : https://partner.skills.google/paths/3667 ○ Getting started with ADK: https://www.skills.google/catalog_lab/32017 ○ Deployment: https://www.skills.google/catalog_lab/32530 ○ Build and deploy multi agent: https://www.skills.google/course_templates/1445 Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, 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 June 2026 totaled $14.8 billion. Disclaimer Privacy Statement Terms of use Sitemap Raise a Grievance We