Senior AI & Machine Learning Engineer / AI Solutions

Job Summary

We are seeking a highly experienced Senior AI & Machine Learning Engineer / AI Solutions Architect with 10–15+ years of IT experience to design, build, and deploy enterprise-scale AI and Machine Learning solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, MLOps, Deep Learning, NLP, Computer Vision, and cloud-based AI platforms.

Key Responsibilities

• Design and develop enterprise AI/ML applications and intelligent automation solutions.
• Build, fine-tune, and optimize Large Language Models (LLMs) and foundation models.
• Develop Retrieval-Augmented Generation (RAG) and AI Agent solutions.
• Design scalable AI architectures for enterprise applications.
• Build and deploy end-to-end ML pipelines from data ingestion to production.
• Develop AI-powered chatbots, copilots, recommendation engines, and predictive analytics solutions.
• Implement prompt engineering and model optimization techniques.
• Deploy AI solutions using MLOps best practices.
• Monitor, evaluate, and improve AI model performance in production.
• Collaborate with Data Engineers, Data Scientists, Software Engineers, and business stakeholders.
• Implement Responsible AI, governance, security, and compliance standards.
• Mentor engineering teams and provide technical leadership.

Required Technical Skills

Programming Languages

• Python (Expert)
• SQL
• Java
• Scala

Artificial Intelligence & Machine Learning

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning
• Transfer Learning
• Fine-Tuning
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents / Agentic AI
• Multi-Agent Systems

AI Frameworks & Libraries

• PyTorch
• TensorFlow
• Keras
• Scikit-learn
• Hugging Face Transformers
• LangChain
• LlamaIndex
• DSPy
• OpenCV

LLM Platforms

• OpenAI
• Azure OpenAI
• Anthropic Claude
• Google Gemini
• Meta Llama
• Mistral AI
• Cohere

MLOps

• MLflow
• Kubeflow
• Azure Machine Learning
• AWS SageMaker
• Google Vertex AI
• Docker
• Kubernetes
• CI/CD for ML Pipelines

Vector Databases

• Pinecone
• ChromaDB
• FAISS
• Weaviate
• Milvus

Data Engineering

• Apache Spark
• Databricks
• Snowflake
• Apache Airflow
• Kafka
• Delta Lake

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (Google Cloud Platform)

Databases

• PostgreSQL
• MongoDB
• MySQL
• Redis

DevOps & Tools

• Git
• GitHub
• Azure DevOps
• Jenkins
• Terraform

Required Qualifications

• Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 10–15+ years of IT experience, including 5+ years in AI/ML or Generative AI.
• Strong expertise in enterprise AI architecture and ML model deployment.
• Experience building production-grade AI and LLM applications.
• Strong knowledge of cloud-native AI services and MLOps.
• Excellent analytical, communication, and leadership skills.

Preferred Experience

• Enterprise AI Copilots and conversational AI.
• RAG-based knowledge management systems.
• AI Agents and workflow automation.
• Fine-tuning open-source LLMs (Llama, Mistral, Falcon).
• Healthcare, Banking, Insurance, Retail, Manufacturing, or Telecom domains.
• AI governance, security, and Responsible AI frameworks.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• NVIDIA Deep Learning Institute Certifications