AI Engineer

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About The Role :

Job Summary

We are seeking a highly skilled AI Engineer experience in Software Development, Data Science, or Machine Learning to design, develop, and deploy cutting-edge AI systems leveraging Large Language Models (LLMs), Chatbots, Retrieval-Augmented Generation (RAG), and agentic AI architectures.

This role involves hands-on development with LLMs, embeddings, RAG pipelines, and multi-agent systems using modern frameworks like LangChain, LangGraph, and LlamaIndex. The ideal candidate has experience with Vertex AI on GCP and IBM WatsonX, fine-tuning, and Agent Development Kits (ADKs), and is excited about building scalable, production-grade AI platforms.

Responsibilities

- Agentic AI Development

Design, build, and deploy

agentic AI systems using frameworks such as LangChain, LangGraph, and related libraries.

Develop and deploy

multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.

- RAG Pipelines:

Implement and optimize

retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for

grounded, accurate responses.

- LLM Engineering:

Fine-tune and prompt-engineer LLMs for

task-specific reasoning, planning, and dynamic adaptation.

Work with

LLM/SLM APIs, embeddings, and advanced generative AI techniques.

- Enterprise AI Platform:

Lead the development of enterprise-grade AI platforms integrating

LLMs, RAG, embeddings, and agentic AI protocols.

Implement and standardize

Model Context Protocol (MCP) for consistent context management across models and agents.

- MLOps & Observability:

Establish and enforce best practices for

MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.

- Applied AI Prototyping:

Rapidly

prototype, experiment, and iterate to improve AI agent capabilities.

- Collaboration & Research:

Participate in the

full research cycleliterature review, data exploration, experimentation, and presentation of findings.

Collaborate effectively with other engineers, researchers, and data scientists.

Contribute to the

documentation and standardization of technical code and practices.

Required Education

Bachelors degree in Computer Science, Engineering, or a related quantitative field.

Masters or Ph.D. is a strong plus.

Required Experience

- 5+ years overall experience in software development, data science, or machine learning.
- 1+ year of hands-on experience developing AI applications with LLMs and systems such as

retrieval-based methods, fine-tuning, or agent-based architectures.
- 1+ year of experience with frameworks like

LangChain, LlamaIndex, OpenAI, or similar tools.

Required Technical Skills

- Strong programming skills in

Python and basics in

SQL.
- Expertise with

LLM/SLM APIs, embeddings, and RAG systems.
- Experience deploying on

Google Cloud Platform (GCP) with

Vertex AI, and

IBM WatsonX.
- Familiarity with

agentic AI protocols and exposure to

Agent Development Kits (ADKs).

Preferred Qualifications

- Experience implementing

Model Context Protocol (MCP) for agent coordination.
- Prior exposure to

LangGraph, AutoGen, or related orchestration frameworks.
- Knowledge of

MLOps best practices (CI/CD for ML, observability, monitoring, scaling).
- Familiarity with

responsible AI principles (safety, fairness, interpretability).
- Experience in

enterprise-scale deployments of AI-driven platforms.
- Contributions to

open-source AI/ML projects are a plus.

Permanent

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