AI Engineer (Startup/ 3-5 years)

PeopleGene; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

PeopleGene in Gurugram is seeking a senior Generative AI/ML engineer to design, train, and optimize GenAI solutions for enterprise use cases, focusing on LLMs, prompts, and automation.

You will build multi-agent, multi-model architectures, implement guardrails, monitor performance, and collaborate with product and engineering teams to deliver production-ready GenAI systems.

Qualifications

• Bachelor’s or Master’s degree in CS, data science, AI or related field.
• 5+ years in data science, ML engineering, or AI development with GenAI focus.
• Strong hands‑on with LLMs, transformers, embeddings, and vector databases.

Responsibilities

• Design, train, fine-tune, and evaluate Generative AI models for enterprise use cases.
• Develop and optimize prompt engineering, RAG pipelines, agents, and fine-tuning workflows.
• Design, develop, and optimize a multi-agent framework for autonomous domain collaboration.
• Work with Open source and commercial LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.).
• Implement guardrails, safety mechanisms, and hallucination mitigation techniques.
• Partner with business, consulting, and product teams to identify GenAI use cases.
• Translate business problems into GenAI solution architectures and success metrics.
• Create blueprints, prototypes, and POCs to demonstrate value.
• Design and manage data pipelines for AI training, fine-tuning, and inference.
• Build scalable, secure GenAI systems for production environments.
• Collaborate with engineering on deployment, monitoring, and retraining strategies.
• Monitor model performance, latency, cost, and drift in production.
• Ensure responsible, ethical, and compliant use of Generative AI.
• Implement explainability, auditability, and traceability where required.
• Address data privacy, IP protection, and regulatory constraints (e.g., GDPR).
• Define and enforce AI best practices, standards, and usage guidelines.

Skills

GenAI frameworks

LLMs

Transformers

Python

LangChain

LlamaIndex

Haystack

Hugging Face

LoRA/PEFT

MLOps

CI/CD

Model monitoring

Vector databases

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, AI

Tools

Python

LangChain

LlamaIndex

Haystack

Hugging Face

LoRA

PEFT

3D deep learning

Job description

• Design, train, fine-tune, and evaluate Generative AI models (LLMs, multimodal models) for enterprise use cases.
• Develop and optimize prompt engineering, RAG pipelines, agents, and fine-tuning workflows.
• Design, develop, and optimize a multi‑agent agentic framework that enables autonomous, domain‑aware collaboration across specialized agents.
• Work with open-source and commercial LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.).
• Implement guardrails, safety mechanisms, and hallucination mitigation techniques.
• Partner with business, consulting, and product teams to identify, evaluate, and prioritize GenAI use cases.
• Translate business problems into clear GenAI solution architectures and success metrics.
• Create solution blueprints, prototypes, and POCs to demonstrate business value.
• Design and manage data pipelines for AI training, fine-tuning, and inference.
• Build scalable, secure, and cost-efficient GenAI systems for production environments.
• Collaborate with engineering teams on deployment, monitoring, and retraining strategies.
• Monitor model performance, latency, cost, and drift in production.
• Ensure responsible, ethical, and compliant use of Generative AI.
• Implement explainability, auditability, and traceability mechanisms where required.
• Address data privacy, IP protection, and regulatory constraints (e.g., GDPR).
• Define and enforce AI best practices, standards, and usage guidelines.

Good to have:

• Prior 3-5 years of experience in data science, ML engineering, or AI development, with 2+ years focused on Generative AI.
• Strong hands‑on experience with LLMs, transformers, embeddings, and vector databases.
• Proficiency in Python and GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face).
• Experience with fine‑tuning techniques (LoRA, PEFT, instruction tuning).
• Experience designing multi‑agent systems, including orchestration, coordination, and distributed reasoning.
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
• Familiarity with 3D deep learning and large scale point cloud processing is a plus.
• Experience working in fast paced startup environment (preferred).
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.