AI Engineer

Job Information

About Us

Job Description

Key Responsibilities

• Build, evaluate, and deploy machine learning and deep learning models for production.
• Develop LLM-based and agentic applications, including RAG pipelines and tool use.
• Fine-tune and optimize models for accuracy, latency, and cost using PEFT and quantisation.
• Design evaluation frameworks, benchmarks, and guardrails to safeguard model quality.
• Build and automate data pipelines for training, inference, and model monitoring.
• Package and serve models as scalable APIs with containerisation, CI/CD, and MLOps.
• Stay updated with advancements in AI/ML and apply them to practical use cases.

Educational Qualifications

• A degree in computer science, information technology, engineering, mathematics, statistics, or a related quantitative field is required.
• Accepted qualifications include B.E., B.Tech, M.Tech, B.Sc., M.Sc., MCA, or an equivalent degree.
• Relevant certifications in cloud, AI/ML, or software engineering are a plus.

Technical Skillset

• Strong Python programming skills and experience with at least one ML/DL framework, such as scikit-learn, PyTorch, or TensorFlow.
• Hands-on experience with LLM APIs, prompt engineering, and agent frameworks such as LangChain, LangGraph, or MCP.
• Working knowledge of RAG, embeddings, and vector databases such as pgvector, FAISS, or Pinecone.
• Experience serving models as APIs with FastAPI and Docker, together with MLOps practices.
• Proficiency with SQL, large-dataset data pipeline tooling, and at least one cloud platform: AWS, Azure, or GCP.

Soft Skills

• Adaptability in a fast-evolving technology landscape.
• Structured, hands-on problem-solving ability.
• Critical thinking to evaluate trade-offs and validate AI-generated outputs.

Benefits

• Opportunity to work in a dynamic, fast-paced engineering IT organization.
• Opportunity to contribute to technology that transforms product development.