Communication Crafts
Website:
communicationcrafts.com
Job details:
We are looking for an experienced
AI Automation Engineer / Python AI-ML Engineer to design, build, and maintain end-to-end AI-driven automation systems. The role involves working with
LLMs (OpenAI),
voice AI (Retell AI),
email/SMS/web chat automation, and
scalable backend services while managing the complete
automation lifecycle from design to production.
Experience: 4-5 years
Key Responsibilities
- Design and implement end-to-end AI automation workflows covering voice, email, SMS, and web chat systems.
- Integrate and customize LLMs (OpenAI and similar) for conversational AI, decision-making, and automation logic.
- Build and manage voice AI solutions using platforms such as Retell AI, including call flows and real-time responses.
- Develop email automation systems for sending, receiving, parsing, classification, and AI-based responses.
- Implement SMS and messaging automation using providers such as Twilio or equivalent platforms.
- Design and develop backend APIs and microservices using Python and FastAPI.
- Apply OOP principles, clean architecture, and modular design in Python codebases.
- Build RAG (Retrieval-Augmented Generation) pipelines using vector databases for context-aware AI responses.
- Train, fine-tune, and evaluate LLM and ML models, ensuring accuracy and performance.
- Deploy AI systems to cloud environments, ensuring scalability, reliability, and security.
- Implement monitoring, logging, analytics, and error handling for production AI workflows.
- Collaborate with product and operations teams to translate business processes into AI automation solutions.
- Continuously optimize AI systems for cost, latency, and response quality.
Must-Have Skills
- Strong experience with LLMs and OpenAI APIs (Chat/Assistants, embeddings, function calling).
- LLM fine-tuning and customization, including dataset preparation and evaluation.
- Expertise in prompt engineering and conversational flow design.
- Proven experience in end-to-end automation design and workflow orchestration.
- Advanced Python development skills with strong OOP concepts and clean coding practices.
- Experience building APIs and AI services using FastAPI.
- Solid understanding of machine learning fundamentals, model training, and evaluation.
- Hands-on experience with RAG architectures and vector databases.
- Experience deploying and monitoring AI systems in cloud environments.
Libraries & Tools (Experience Required)
- The candidate should have experience with LLM and generative AI libraries such as OpenAI Python SDK, LangChain, LlamaIndex, Hugging Face Transformers, and SentenceTransformers.
- The candidate should be proficient in machine learning and deep learning libraries including NumPy, Pandas, scikit-learn, PyTorch, TensorFlow/Keras, XGBoost, and LightGBM.
- The candidate should have hands-on experience with RAG architectures and vector databases such as FAISS, Pinecone, Weaviate, ChromaDB and ect.
- The candidate should be skilled in backend and API development using FastAPI, Pydantic, Flask, and ASGI servers like Uvicorn or Gunicorn.
- The candidate should be familiar with automation and system integration tools including Requests/HTTPX, Celery or RQ, Redis, REST APIs, and webhooks.
- The candidate should have experience working with voice, messaging, and communication platforms such as Retell AI, Twilio (SMS and Voice), SMTP/IMAP email libraries, and WebSocket-based communication.
- The candidate should be experienced in database and storage technologies including PostgreSQL, MySQL, MongoDB, SQLAlchemy, and vector database clients.
- The candidate should have exposure to DevOps and cloud tooling such as Docker, Git, CI/CD pipelines, and cloud provider SDKs (AWS, GCP, or Azure).
- The candidate should be familiar with monitoring, observability, and testing frameworks including Prometheus, Grafana, OpenTelemetry, Sentry, PyTest, and unit testing tools.
Click on Apply to know more.