{"id":1594559,"url":"https://alion.io/job/hcltech-senior-technical-specialist-16","title":"Senior Technical Specialist","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Sales","role_family":"Sales","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":38000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic 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Learning","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-10-01T17:24:36Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-13T15:03:25Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"Job Summary\nDesign, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise\nIdentify need for Pro Code Vs No Code design based on customer’s problem statement and data sources\nDesign Deploy and custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise\nBuild native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery.\nArchitect scalable short-term session storage, conversation state persistence, and long-term memory architectures across multi-agent interactions.\nImplement 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.\nEnforce fine-grained Access Control Lists (ACLs), user/group permission inheritance, and data governance policies to ensure agents strictly adhere to enterprise access boundaries.\nUtilize developer tooling including Agent CLI and Antigravity for local rapid prototyping, testing, emulation, distributed tracing, and root cause analysis (RCA).\nArchitect Human-in-the-Loop (HITL) workflows, ensuring seamless Interrupt and Resume patterns between autonomous agents and human experts for critical decision points.\nBuild 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.\nImplement advanced reasoning patterns such as Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection to enhance agent reliability.\nEstablish quantitative evaluation frameworks to measure agent trajectories, tool invocation precision/recall, and reasoning faithfulness.\nCollaborate directly with client engineering and architecture teams to deploy, validate, and operationalize enterprise agentic AI solutions in client environments.\nKey Responsibilities\nDesign, develop, and deploy production-grade Multi-Agent Systems (MAS) and agentic workflows using Gemini Enterprise\nIdentify need for Pro Code Vs No Code design based on customer’s problem statement and data sources\nDesign Deploy and custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise\nBuild native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery.\nArchitect scalable short-term session storage, conversation state persistence, and long-term memory architectures across multi-agent interactions.\nImplement 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.\nEnforce fine-grained Access Control Lists (ACLs), user/group permission inheritance, and data governance policies to ensure agents strictly adhere to enterprise access boundaries.\nUtilize developer tooling including Agent CLI and Antigravity for local rapid prototyping, testing, emulation, distributed tracing, and root cause analysis (RCA).\nArchitect Human-in-the-Loop (HITL) workflows, ensuring seamless Interrupt and Resume patterns between autonomous agents and human experts for critical decision points.\nBuild 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.\nImplement advanced reasoning patterns such as Chain-of-Thought (CoT), ReAct, Plan-and-Solve, and Self-Reflection to enhance agent reliability.\nEstablish quantitative evaluation frameworks to measure agent trajectories, tool invocation precision/recall, and reasoning faithfulness.\nCollaborate directly with client engineering and architecture teams to deploy, validate, and operationalize enterprise agentic AI solutions in client environments.\nSkill Requirements\nMust-Have Skills\nCore 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.\nGemini & 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).\nMemory & 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).\nThird 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.\nAuth & 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).\nACLs & Permissions: Deep working knowledge of enterprise Access Control Lists (ACLs), identity federation, permission trimming, and role-based access control (RBAC) across heterogeneous data sources.\nDeveloper Tooling: Proficiency in developer tooling such as Agent CLI and Antigravity for local simulation, debugging, prompt engineering, and execution graph tracing.\nCI/CD & DevOps: Proven track record of configuring and maintaining automated CI/CD pipelines (Cloud Build, GitHub Actions) for agent containerization, deployment, and test automation.\nEvaluation & Debugging: Practical knowledge of AI evaluation methodologies, trajectory analysis, and performing root cause analysis (RCA) on agent execution failures, tool errors, and prompt regressions.\nClient Collaboration: Strong technical communication, consulting acumen, and client-facing collaboration skills within an Agile environment.\nGood-to-Have Skills\nExperience with inter-agent communication protocols such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) architectures.\nExperience integrating agents with Enterprise Knowledge Graphs, structured ontologies, and hybrid vector search systems.\nExperience with enterprise data security frameworks such as Sensitive Data Protection (SDP/DLP) and VPC Service Controls (VPC-SC).\nQualifications and Prior Experience\nExperience in software development, cloud solution architecture, and AI engineering (preferably on Google Cloud Platform).\nProven track record of designing, building, and deploying production AI agents or enterprise GenAI solutions using ADK, Vertex AI, or Gemini.\nHands-on experience in customer-facing technical delivery, solutions engineering, or forward-deployed engineering (FDE) roles.\nFamiliarity with enterprise Agile development lifecycles, sprint delivery, and stakeholder management.\nOther Requirements\nCertifications and Trainings\nProfessional Machine Learning Engineer\nGoogle Skill Boost labs/course\nIntroduction to Gemini Enterprise :\nhttps://partner.skills.google/course_templates/1401\nGemini Enterprise and NotebookLM :\nhttps://partner.skills.google/paths/3667\nGetting started with ADK:\nhttps://www.skills.google/catalog_lab/32017\nDeployment:\nhttps://www.skills.google/catalog_lab/32530\nBuild and deploy multi agent:\nhttps://www.skills.google/course_templates/1445","description_format":"text","description_chars":7710,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-01T17:24:36Z"}],"visa":[],"liveness":{"score":84,"band":"hot","label":"Hiring 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