Senior AI/ML Engineer - RAG/Agentic AI

ROLE OVERVIEW :

We are looking for a hands-on AI/ML Engineer with strong GenAI, LLM, and Agentic AI experience to build the intelligence layer of the ConX AI platform.

You will be responsible to lead the fine-tuning, orchestrating, and operationalising LLMs and agentic workflows, working closely with platform engineers and founders to build enterprise-ready, scalable AI systems.

This role is focused on applied AI and production, not academic research.

KEY RESPONSIBILITIES :

LLM & GenAI Engineering :

- Fine-tune and customize Large Language Models (open-source and proprietary) for enterprise use cases

- Design prompt strategies, retrieval-augmented generation (RAG), and tool-augmented LLM workflows

- Optimize LLM performance for latency, cost, accuracy, and reliability

- Evaluate and benchmark models across tasks and domains

Agentic AI & Workflow Orchestration :

- Design and build agentic AI systems with multi-step reasoning, planning, and tool usage

- Implement autonomous and semi-autonomous AI agents for enterprise workflows

- Build orchestration logic for agent-to-agent and agent-to-tool interactions

- Implement guardrails, fallbacks, and human-in-the-loop mechanisms

AI Platform & Integration :

- Expose AI capabilities via scalable APIs for the ConX platform

- Integrate AI services with platform modules built by Full Stack engineers

- Work on context management, memory systems, and conversation state handling

- Enable configuration-driven AI behaviour per client or use case

Model Ops & Deployment (MLOps / LLMOps) :

- Package, deploy, and monitor AI models in production environments

- Work closely with DevOps to manage inference pipelines and scalability

- Implement logging, evaluation, drift detection, and feedback loops

- Ensure compliance, data security, and responsible AI practices

Collaboration & Knowledge Sharing :

- Participate in product, architecture, and roadmap discussions

- Mentor the AI/ML Intern and guide experimentation

- Stay updated with evolving GenAI and Agentic AI advancements

REQUIRED SKILLS & EXPERIENCE :

Must-Have :

- 3+ years of experience in AI/ML engineering or applied data science

- Strong hands-on experience with GenAI and LLMs

- Experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face, etc.)

- Practical experience with :

a. Prompt engineering

b. Fine-tuning or adapter-based training

c. RAG pipelines

- Experience deploying AI models into production environments

- Strong understanding of NLP fundamentals and transformer architectures

- Experience building Agentic AI systems or autonomous agents

- Familiarity with LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks

- Experience with vector databases and embeddings

- Knowledge of speech-to-text or text-to-speech systems

- Prior experience in enterprise or BFSI AI use cases

- Good Academic Background

MINDSET & TRAITS :

- Product-focused AI mindset (accuracy + reliability over demos)

- Ability to balance experimentation with production stability

- Comfort working in fast-paced startup environments

- Strong problem-solving and systems thinking

- Willingness to own outcomes end-to-end

COMPENSATION & GROWTH :

- Compensation will be as per industry standards and aligned with the candidates experience, and role impact

- Performance-linked growth and role expansion

WHY JOIN QUBELABS AI :

- Build real-world Agentic AI systems, not just prototypes

- High ownership of AI architecture and roadmap

- Work closely with founders and platform engineers

- Opportunity to shape a global, enterprise-grade AI product

REPORTING TO : Founders QubeLabs AI