Technical Consultant

Technology, Data & Digital · Data, AI & Analytics · Artificial Intelligence · Machine Learning

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HCLTech is seeking a Technical Consultant with 2-5 years of experience to design, develop, and deploy Generative AI solutions using Large Language Models (LLMs). The role involves building AI-powered applications, APIs, and integrations, implementing prompt engineering and RAG, and deploying solutions on cloud platforms like Azure, AWS, or GCP. Collaboration with stakeholders to translate use cases into AI solutions is key.

Job Summary

The GenAI Engineer will be responsible for designing, developing, and deploying AI-powered solutions using Large Language Models (LLMs) and modern Generative AI frameworks. The role focuses on building scalable, production-ready AI applications and integrating them into enterprise ecosystems.

AI engineers in current enterprise setups are primarily expected to build LLM-based applications, APIs, and AI-driven workflows rather than core model development.

Key Responsibilities

Design and develop GenAI solutions using LLMs and AI frameworks
Build AI-powered applications, APIs, and integrations with enterprise systems [We are loo...Role: Gen | Viva Engage]
Implement prompt engineering, RAG (Retrieval-Augmented Generation), and workflow orchestration
Fine-tune and optimize models where required (performance, latency, cost optimization) [We are loo...Role: Gen | Viva Engage]
Deploy solutions on cloud platforms (Azure/AWS/GCP) and ensure scalability
Monitor model performance and continuously improve outputs
Ensure adherence to Responsible AI principles (security, fairness, governance) [We are loo...Role: Gen | Viva Engage]
Collaborate with stakeholders (business + technical) to translate use cases into AI solutions

Skill Requirements

Experience: ~2–5 years (with exposure to AI/LLMs)

Technical Skills Required

Core GenAI Skills

Strong understanding of LLMs, prompt engineering, embeddings
Experience with:
- OpenAI / Azure OpenAI / Gemini / Anthropic APIs
- LangChain / LangGraph / LLM orchestration frameworks
Knowledge of:
- RAG, vector databases, knowledge retrieval systems

Programming & Development

Proficiency in Python
Experience in building APIs (FastAPI / Flask / Django)
Experience in building production-grade applications

AI/ML Foundations

NLP, deep learning basics, ML pipelines
Exposure to model fine-tuning techniques (LoRA, PEFT, etc.) is an advantage

Cloud & DevOps

Cloud platforms: Azure / AWS / GCP
Familiarity with:
- Docker / Kubernetes
- CI/CD pipelines

Other Requirements

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