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HC
HCLTech

Senior Technical Specialist

Bengaluru · Director

Good timing - competition is buildingVerified listingPosted 5d ago

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86Overall
64Skills
97Experience

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Skills required

19 listed
Retrieval-Augmented Generation (RAG)Large Language Models (LLMs)CI/CDPrompt EngineeringAzure OpenAI ServiceMarket TrendValue CreationAngular (Web Framework)+11 more
Retrieval-Augmented Generation (RAG)Large Language Models (LLMs)CI/CDPrompt EngineeringAzure OpenAI Service

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Job description

Job Summary

Role Summary

The AI Fullstack Engineer designs, builds, and delivers end-to-end AI-powered applications by combining modern frontend frameworks with backend services and Generative AI capabilities. This role focuses on integrating Large Language Models (LLMs) into real user experiences such as copilots, AI assistants, and intelligent workflows, while ensuring scalability, performance, and usability.

Key Responsibilities

• Build end-to-end AI-powered applications using modern frontend and backend technologies.
• Integrate Large Language Models (LLMs) into user-facing workflows and experiences.
• Develop AI-enabled features such as chat interfaces, copilots, summarization, and intelligent search.
• Design and implement responsive UIs using React, Angular, or similar frameworks.
• Build backend services and APIs to orchestrate LLM calls, RAG pipelines, and AI workflows.
• Implement prompt engineering, embeddings, and Retrieval-Augmented Generation (RAG).
• Ensure application performance, scalability, security, and reliability.
• Collaborate with UX designers, AI engineers, and product teams.

Required Skills & Experience

• Strong experience with frontend frameworks such as React or Angular.
• Backend development experience using Python, Node.js, or Java.
• Hands-on experience integrating LLMs (OpenAI, Azure OpenAI, Gemini, Claude, or open-source models).
• Experience with prompt engineering, embeddings, and RAG pipelines.
• Familiarity with REST/GraphQL APIs, Docker, cloud platforms, and CI/CD pipelines.
• Basic exposure to MLOps or LLMOps concepts is a plus.

Experience Level

• 11–13 years of fullstack or application engineering experience.
• 1–3+ years of hands-on experience delivering AI or GenAI-enabled applications.

Success Measures

• AI features seamlessly integrated into production user workflows.
• High adoption and usability of AI-powered applications.
• Stable, scalable, and secure fullstack AI solutions running in production.

Key Responsibilities

1. To architect| design and develop (through Team) solution for product/project & sustenance delivery
2. To support as an Subject Matter Expert
3. To ensure knowledge up-gradation and work with new technologies so that the solution is current and meets quality standards and the client requirements
4. Ensuring a sufficient pool of skilled professionals in the designated technology, through activities such as conducting interviews, providing training sessions and offering mentorship.
5. To gather specifications and deliver solutions to the client organization based on understanding of a domain or technology.
6. To support competency development with envisioning and articulating propositions – building collaterals/ whitepaper creation, market trend analysis etc.
7. To recommend client value creation initiatives and implement industry best practices (on specific technology/product)

Skill Requirements

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Other Requirements

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Two ways in

Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

Free · no signup

Get tomorrow's jobs before you have to search

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Join WhatsAppJoin Telegram

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Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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