Artificial Intelligence Consultant

Job Title:

Experience:

Employment Type:

About the Role

AI Engineer

AI-powered systems

Key Responsibilities1. Machine Learning & Deep Learning

• Design, train, and optimize models using

  supervised, unsupervised, and reinforcement learning

  techniques.
• Build and deploy

  neural networks

  with frameworks such as

  TensorFlow, PyTorch, and Keras

  .
• Perform

  LLM fine-tuning, optimization, and prompt engineering

  for specific business use cases.
• Evaluate model performance through metrics, testing, and validation techniques.

2. Data Handling & Preprocessing

• Perform

  data cleaning, transformation, and preprocessing

  using

  NumPy, Pandas, and Scikit-learn

  .
• Develop

  feature engineering pipelines

  for large and complex datasets.
• Create

  data visualizations

  using

  Matplotlib

  and

  Seaborn

  to communicate model insights effectively.

3. Natural Language Processing (NLP)

• Build and enhance

  NLP applications

  such as chatbots, text classification, and sentiment analysis systems.
• Work with

  LLMs (GPT, BERT)

  and implement

  Named Entity Recognition (NER)

  , topic modeling, and document summarization.
• Develop

  context-aware prompt systems

  and fine-tune transformer-based models.

4. AI Agent Development

• Design and build

  stateful, multi-step AI agents

  using

  LangGraph

  or similar frameworks.
• Implement

  workflow orchestration

  ,

  tool integrations

  , and

  memory management

  for dynamic agent behavior.
• Build

  autonomous AI systems

  that interact with APIs, databases, and real-time data streams.

5. Cloud Platforms & MLOps

• Deploy and manage AI models on

  AWS, Azure, or GCP

  environments.
• Containerize and scale applications using

  Docker

  and

  Kubernetes

  .
• Implement

  CI/CD pipelines

  ,

  model versioning

  , and

  automated monitoring

  for production models.

6. Voice Agent Specialization

• Develop

  end-to-end voice AI pipelines

  integrating

  ASR (Automatic Speech Recognition)

  and

  TTS (Text-to-Speech)

  modules.
• Work on

  real-time conversational AI systems

  optimized for low latency and high accuracy.
• Design

  context-aware, adaptive voice agents

  that maintain conversational flow and memory.

Technical Skills Required

Primary Skills:

• Python

  (Core Programming, ML Libraries, Automation)

Secondary Skills:

• Node.js

  (for backend AI integrations, API design)

Bonus Skills:

• R

  ,

  SQL

  (for statistical analysis and data querying)

Core Technologies:

• TensorFlow, PyTorch, Keras, Scikit-learn
• NumPy, Pandas, Matplotlib, Seaborn
• LangGraph, LangChain
• OpenAI API, Hugging Face Transformers
• Docker, Kubernetes, Git, CI/CD Pipelines

Qualifications

• Bachelor’s or Master’s degree in

  Computer Science, Artificial Intelligence, Data Science, or related fields

  .
• 2–4 years of hands-on experience in

  AI/ML model development and deployment

  .
• Proven experience working on

  LLMs, voice AI, or AI agent systems

  .

Preferred Experience

• Experience integrating AI into

  web-based or cloud-native applications

  .
• Familiarity with

  vector databases

  (e.g., Pinecone, Weaviate, FAISS) for semantic search.
• Knowledge of

  real-time data streaming

  and

  API-driven architecture

  .
• Exposure to

  generative AI models

  (ChatGPT, Claude, Gemini, etc.).

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and documentation skills.
• Ability to collaborate across technical and product teams.
• Proactive approach toward learning and implementing emerging AI technologies.

Perks & Benefits

• Competitive salary and performance-based rewards.
• Opportunity to work on

  cutting-edge AI/LLM projects

  .
• Continuous learning, mentorship, and R&D exposure.
• Innovative and growth-oriented work culture.