Generative AI Engineer III
Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Software Engineering
In short
We are seeking a Generative AI Engineer III with strong Python skills to act as an embedded AI expert in a product team. You will design, develop, and optimize GenAI and Agentic AI applications, integrate LLMs, and mentor other developers on AI concepts.
Responsibilities
- Act as the squad's embedded GenAI expert and single point of contact for all AI/GenAI-related decisions, implementation, and guidance.
- Design, develop, and optimize production-grade GenAI and Agentic AI applications, services, and pipelines in Python.
- Interpret architectural blueprints and implement complex GenAI components, ensuring alignment with enterprise standards.
- Integrate Large Language Models (LLMs) — including OpenAI, Azure OpenAI, Hugging Face, Anthropic, and Cohere — into enterprise workflows and products.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration systems, and Agentic AI flows.
- Build, maintain, and evolve APIs, automation scripts, and AI pipelines on the AIForce platform.
- Train and mentor squad members (backend, frontend, full-stack developers) on GenAI concepts, tools, frameworks, and best practices.
- Conduct LLM performance evaluation, prompt optimization, and model fine-tuning as required.
- Champion Safe AI, AI governance, and responsible AI development practices across the squad.
- Monitor, test, and troubleshoot deployed GenAI models and services in production environments.
- Stay current with emerging GenAI frameworks, LLM advances, and industry trends; proactively assess and introduce relevant innovations.
Requirements
- Strong proficiency in Python (3+ years), including experience building production-grade applications.
- Proven hands-on experience with Agentic AI and GenAI frameworks: LangChain, LlamaIndex, Hugging Face Transformers, AutoGen, CrewAI, or similar.
- Demonstrated experience designing and implementing RAG architectures, vector search pipelines, and multi-agent systems.
- Familiarity with LLM APIs: OpenAI, Azure OpenAI, Anthropic, Cohere, and open-source models.
- Experience with vector databases (e.g., Pinecone, Weaviate, Azure AI Search, FAISS, Chroma).
- Strong knowledge of prompt engineering, chain-of-thought techniques, and LLM evaluation/observability methods.
- Knowledge of Safe AI principles, AI security, AI governance frameworks, and responsible AI development practices.
- Hands-on experience with developing AI solutions on any cloud platform.
- Solid software engineering fundamentals: Git, CI/CD pipelines, automated testing, API design.
- Effective communication and mentoring skills — able to explain complex AI concepts to non-AI developers clearly.
Desired Qualifications
- Understanding of LLM fine-tuning approaches (RLHF, PEFT, LoRA) — practical experience will be added advantage.
- Experience with MLOps tooling (MLflow, Azure ML Pipelines, or equivalent).
- Exposure to multimodal models (vision-language models, speech-to-text integration).
- Prior experience working as an AI champion or tech lead within a cross-functional product team.
- Familiarity with enterprise AI governance and compliance frameworks.
Benefits
- Opportunity to work as an embedded AI expert within a product team.
- Influence on AI strategy and implementation.
- Mentorship and training opportunities for team members.
- Exposure to various LLMs and AI platforms.
- Work on enterprise-grade solutions.
- Global technology company with diverse industry experience.
#Generative AI#AI#Python#Machine Learning#LLM#Agentic AI#RAG#Cloud
Company
HCLTech
Job Posted
3 days ago
Employment Type
Full Time
WorkMode
On Site
Experience Level
Mid-Senior
Locations
Noida, India
Pune, India
Applicants
Be an early applicant