Lead Administrator (Support &Operations)
HCLTech
Gautam Buddha Nagar, Uttar Pradesh, IndiaPosted Discovered via the company's careers siteMatch locked
Full-time3+ years exp
Job Summary
Applied AI Technologist
(AI Experience Technologist)
About the role
We're looking for an Applied AI Technologist who can turn a customer's business problem into a working, production-ready AI solution. You'll work at the point where customer conversations and hands-on building meet. You'll understand what the customer needs, picture the end state, build it quickly with AI-assisted development, and make sure it holds up in a real enterprise environment.
This is a builder role for someone with sound engineering judgment. Vibe coding lets you move fast, and your fundamentals decide what is good enough to ship.
Experience : 3 to 10 years
Customer and requirements
- Work directly with customers to understand their business problems, clarify vague requirements, and turn them into clear solution outcomes.
- Picture the end state for customers and end users, and show it early with prototypes, mockups and demos.
- Get up to speed quickly on new domains and customer contexts, and know when to bring in specialists.
- Explain solutions, trade-offs and risks clearly to both business and technical stakeholders.
Building with AI
- Design and build solutions quickly with AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot).
- Guide LLMs precisely, with structured prompting, context engineering and step-by-step iteration, so the output is accurate and consistent.
- Build LLM-powered applications, including agentic workflows, RAG pipelines and tool or function-calling integrations where relevant.
- Design user experiences that are intuitive, useful and fit how end users actually work.
Engineering quality and production readiness
- Review, test, debug and harden AI-generated code. Understand what the AI produced before shipping it, and reject what doesn't meet the bar.
- Take solutions from prototype to production: deployment, integration with customer systems (APIs, identity, data sources) and maintainable handover.
- Design evaluations, test cases and guardrails to measure and improve LLM output quality, reliability and safety.
- Apply security, data-privacy and responsible-AI practices in every solution, especially when handling customer data.
Required skills and experience
•
Programming
Strong hands-on experience in Python and/or front-end (React, JavaScript/TypeScript) or back-end development, with solid software engineering fundamentals: code structure, testing, debugging, version control and basic architecture.
•
AI-assisted development
Expert in vibe-coding workflows. Can break problems into steps, steer AI agents effectively, and review output critically.
•
Prompting and LLM steering
Deep expertise in prompt design, including system prompts, few-shot examples, reasoning techniques, structured outputs, tool use and context management.
•
LLM evaluation
Experience defining success criteria, building test sets and evaluating model output systematically.
•
Deployment and integration
Working knowledge of at least one cloud platform (Azure, AWS or GCP), APIs, containers or serverless, and CI/CD basics.
•
Security and responsible AI
Understanding of data privacy, PII handling, access control, prompt-injection risks and enterprise compliance.
•
Communication
Excellent written and spoken English. Can explain complex ideas clearly and concisely, and present with confidence to customers.
•
Mindset
Learns fast, takes ownership of outcomes, and knows what AI should and shouldn't be used to build.
Nice to have
- Experience with agentic frameworks (e.g., LangGraph, CrewAI, Semantic Kernel, MCP) or enterprise AI platforms (Azure AI Foundry, Copilot Studio, AWS Bedrock, Vertex AI).
- Experience in a customer-facing, consulting or pre-sales role.
- A background in UX, design thinking or product management.
- A portfolio of AI solutions, demos or open-source work that you've built and deployed.
Selection process
•
Screening conversation
background, communication and customer orientation.
•
Live build exercise (90–120 minutes)
Candidates get a deliberately vague customer brief. They are expected to:
•
- ask questions to clarify the requirement
- build a working solution using AI tools of their choice
- walk through what they built and what they would fix, secure or test before production.
•
Customer-scenario discussion
role-play presenting the solution to a business stakeholder.
Not included in the source posting: about the role, benefits.
Skills
artificial-intelligencellmawsazureci-cdgcpjavascriptproduct-managementpythonragreactserverless
Who can apply
The employer didn't state any visa, work authorization, citizenship or clearance requirements in this posting. Confirm with the employer before applying.
Read automatically from the employer's posting text. Always confirm with the employer — requirements can change after a job is published.