We're looking for an AI Engineer to design, build, and ship production-grade AI systems from LLM-powered features to the infrastructure that supports them. You'll work at the intersection of machine learning, software engineering, and product, turning research and prototypes into reliable, scalable systems that real users depend on.
This is a hands-on role for someone who enjoys building end-to-end: from model selection and prompt/architecture design through deployment, monitoring, and iteration.
What You'll Do
- Design, build, and deploy AI/ML-powered features and services into production
- Develop and optimize LLM-based applications, including prompt engineering, retrieval-augmented generation (RAG), and agentic workflows
- Fine-tune, evaluate, and benchmark models against product and business requirements
- Build and maintain data pipelines, embeddings stores, and vector databases that power AI features
- Collaborate with product and design to translate ideas into technical specs and shippable features
- Own the full lifecycle: experimentation, evaluation, deployment, monitoring, and iteration
- Implement robust evaluation frameworks to measure model quality, latency, cost, and safety
- Monitor production systems for performance, drift, and failure modes; troubleshoot and resolve issues
- Write clean, well-tested, maintainable code and contribute to engineering best practices
- Stay current with the AI/ML landscape and evaluate new tools, models, and techniques for adoption
Required Qualifications
- 3+ years of experience in software engineering, with at least 1–2 years working on ML/AI systems in production
- Strong programming skills in Python (and/or [additional language, e.g., TypeScript/Go])
- Experience working with LLM APIs (e.g., OpenAI, Anthropic) or open-source model frameworks
- Familiarity with ML fundamentals: model training, evaluation, fine-tuning, and deployment
- Experience with RAG pipelines, vector databases (e.g., Pinecone, Weaviate, pgvector), and embedding models
- Solid understanding of software engineering fundamentals: version control, testing, CI/CD, API design
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes)
- Strong problem-solving skills and ability to work through ambiguous, evolving requirements
- Excellent communication skills and ability to collaborate across engineering, product, and design
Preferred Qualifications
- Experience building and orchestrating multi-agent or tool-using AI systems
- Familiarity with ML frameworks (PyTorch, TensorFlow) and experiment tracking tools (Weights & Biases, MLflow)
- Experience with prompt evaluation frameworks and LLM observability tools (e.g., LangSmith, Arize, Braintrust)
- Background in data engineering or MLOps
- Contributions to open-source AI/ML projects
- Advanced degree in Computer Science, Machine Learning, or a related field (not required)
Tech Stack:
Python · PyTorch/TensorFlow · LLM APIs (OpenAI/Anthropic) · LangChain/LlamaIndex · Vector DBs · Docker/Kubernetes · AWS/GCP · PostgreSQL · FastAPI
Pay: ₹10,000.00 - ₹40,000.00 per month
Work Location: In person
