AI/ML Engineer
At a glance
Mid-level Machine Learning Engineering role at Fa Ewjt Saasfaprod1. Noida · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI applications in Python and FastAPI, then take them through testing and deployment in CI/CD
- Design LLM workflows for bringing in data, running inference and producing responses
- Use GCP services such as Vertex AI, Cloud Run or Functions, BigQuery and Cloud Storage
- Add embeddings and vector stores to support semantic search and RAG, and connect AI systems to enterprise platforms
- Apply prompt techniques and orchestration frameworks to improve LLM responses and coordinate complex workflows
What you bring
- At least two years developing AI solutions, particularly those built around LLMs
- Strong Python and FastAPI skills for building APIs, plus practical use of GCP services
- Hands-on work with prompt engineering, vector databases and RAG systems
- Familiarity with LLM orchestration frameworks, Git and CI/CD, alongside sound software engineering fundamentals
Who this fits
This mid-level role suits someone who has built LLM-based AI solutions and can work across application development, cloud services and retrieval workflows. The role is hybrid in Noida, India.
From the employer
1. Build production-ready AI applications using Python and FastAPI.
2. Design LLM pipelines including data ingestion, inference, and response generation.
3. Leverage GCP tools like Vertex AI, Cloud Run/Functions, BigQuery, and Cloud Storage.
4. Apply advanced prompt engineering techniques to enhance LLM outputs.
5. Implement vector stores and embeddings for semantic search and RAG.
6. Use orchestration frameworks (e.g., LangChain, LangGraph, CrewAI) for complex workflows.
7. Integrate AI systems with enterprise platforms and maintain robust data flows.
8. Follow best practices in coding, testing, and deployment within CI/CD pipelines.
9. Continuously explore and recommend emerging tools and AI technologies.
1. 2+ years of experience developing AI solutions, especially with LLMs.
2. Proficient in Python and FastAPI for API development.
3. Hands-on experience with GCP services (Vertex AI, Cloud Run/Functions, etc.).
4. Strong prompt engineering skills (e.g., CoT, few-shot, instruction tuning).
5. Experience with vector databases and RAG systems.
6. Familiarity with LLM orchestration frameworks.
7. Solid understanding of software engineering fundamentals.
8. Proficient with Git and CI/CD practices.
1. Bachelors or Masters in Computer Science
2. Experience with MLOps for model deployment and monitoring.
3. Knowledge of distributed systems and data processing.
4. Contributions to open-source projects or strong AI project portfolio.
5. Strong communication skills and ability to explain technical concepts clearly.