Job Overview

Key Responsibilities

Build end-to-end AI solutions using commercial and open-source tools.

Design agent-based AI platforms using frameworks such as LangGraph, AutoGen, and CrewAI.

Translate business objectives into technical requirements and AI solution designs.

Define AI reference architectures, roadmaps, best practices, and implementation standards.

Set up data pipelines, model training environments, CI/CD workflows, and monitoring frameworks.

Drive scalable deployment using Docker, Kubernetes, and cloud platforms.

Manage AI project execution, technical planning, resource coordination, and delivery risks.

Mentor engineering teams and lead technical knowledge-sharing sessions.

Mandatory Skills

Strong hands-on experience with LangGraph, AutoGen, and CrewAI.

Strong programming experience in Python.

Experience with TensorFlow, PyTorch, and Keras.

Robust knowledge of Deep Learning, NLP, RNN, CNN, LSTM, and Transformer-based models.

Experience with AWS, Azure, or Google Cloud Platform.

Experience with Docker, Kubernetes, Jenkins, and GitLab CI/CD.





Knowledge of Terraform and CloudFormation.

Experience with databases such as PostgreSQL, MongoDB, and Cassandra.

Strong understanding of REST APIs, GraphQL, Microservices, and distributed systems.

Experience with messaging systems such as Kafka and RabbitMQ.

Preferred Skills

Experience with Hugging Face and OpenAI APIs.

Hands-on experience in MLOps or LLMOps.

Experience with LLM fine-tuning using models such as GPT, Llama, or PaLM.

Experience with monitoring tools such as Prometheus, Grafana, and ELK Stack.

Cloud certifications in AWS, Azure, or GCP are preferred.

TOGAF certification is desirable.

Qualifications

Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.

Minimum 10 years of experience in AI, Machine Learning, Data Engineering, or related technology domains.

Excellent communication skills and ability

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