We are seeking a highly skilled AI Developer to design, build, and deploy intelligent autonomous systems. This cutting-edge role involves developing AI-powered agents leveraging LLMs (Large Language Models), reinforcement learning, and multi-agent systems, and will utilize frameworks like LangChain, AutoGen, and CrewAI within MLOps pipelines for scalable deployment.

Roles and Responsibilities

AI & Machine Learning Development:

Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models.
Implement LLMs, NLP (Natural Language Processing), reinforcement learning (RL), and computer vision (CV) models.
Optimize retrieval-augmented generation (RAG) systems using vector databases like FAISS, Pinecone, and Chroma.
Work on multimodal AI systems integrating text, image, and audio processing.

Agentic AI Systems Development:

Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments.
Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, and MetaGPT.
Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment.

Software Engineering & MLOps:

Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines.
Implement MLOps workflows for continuous training, monitoring, and model retraining.
Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing.

AI Governance & Security:

Implement AI safety measures, including adversarial defense and bias mitigation.
Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles.
Secure AI agents against prompt injection, model poisoning, and adversarial attacks.

Skills Required

Strong programming skills in Python, Java, or R.
Expertise in machine learning frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude).
Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen).
Knowledge of reinforcement learning algorithms (PPO, A3C, DDPG, SAC).
Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs.
Strong foundation in MLOps and cloud AI services (AWS, Azure AI, Google Vertex AI).
Strong analytical and problem-solving skills.
The ability to work effectively in a fast-paced, cross-functional team.
Excellent communication and documentation skills.
A Master's in Computer Science, AI, or Data Science is preferred.
Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer) are a plus.
Experience with autonomous systems, robotics, or digital twins is preferred.
A minimum of 5-7 years of similar or equivalent experience.