Roles & Responsibilities
3-6 yrs into Development and deployment AI/ML models for use cases such as prediction, recommendation, classification, and anomaly detection across business functions.
Build agentic AI systems that can autonomously execute multi-step workflows (e.g., data ingestion, reasoning, decision-making, and action execution) using modern agent frameworks.
Design, fine-tune, and evaluate LLM-based solutions for tasks like document understanding, question answering, summarization, and conversational assistants.
Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases to ground LLMs on domain-specific content and internal knowledge bases.
Collaborate with product managers, domain experts, data engineers, and software developers to translate business requirements into robust AI solutions and APIs.
Develop and optimize prompt engineering strategies, including structured prompts, tool-calling, and multi-agent coordination for reliable outcomes.
Integrate AI models and services into existing platforms via REST/GraphQL APIs, microservices,



and event-driven architectures.
Apply MLOps best practices for experiment tracking, versioning, CI/CD, monitoring, and observability of models and AI agents in production.
Ensure robust data governance, privacy, and security practices when working with sensitive or proprietary data.
Stay current with advancements in AI/ML, LLMs, agentic AI, and related tools to continuously improve solution quality and performance.

Desired Skills:
AI/ML Core
Solid understanding of supervised, unsupervised, and deep learning techniques; familiarity with reinforcement learning is a plus.
Hands-on experience with common ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
Experience working with structured and unstructured data, including feature engineering, model evaluation, and performance optimization.

LLMs, NLP & Agentic AI
Experience fine-tuning and deploying LLMs (e.g., GPT-family models, Llama,

📌 AIML Engineer (Noida)
🏢 BDO India
📍 Noida