Role Overview The Senior AI / ML Engineer (Agentic Systems & Core ML) is a pivotal role designed for an engineer who excels at the intersection of traditional machine learning and the emerging frontier of autonomous agentic systems. You will be responsible for designing, developing, and deploying sophisticated AI solutions that range from classic computer vision models to complex Multi-Agent Systems that reason, plan, and execute tasks autonomously. This role requires a deep understanding of Large Language Model (LLM) orchestration alongside a rigorous foundation in statistical learning and MLOps.

Key Responsibilities

Agentic Systems & Orchestration

● Design and implement Multi-Agent Systems (MAS) utilizing frameworks such as ADK, LangGraph, CrewAI, or AutoGen to solve complex, multi-step business logic.

● Develop advanced reasoning patterns including Chain-of-Thought, ReAct,

and Reflexion to enhance agent reliability and decision-making.

● Architect Retrieval-Augmented Generation (RAG) pipelines with vector databases to provide agents with contextual enterprise knowledge.

Core Machine Learning & Computer Vision

● Build and refine traditional ML models (Gradient Boosted Trees, Random

Forests, SVN) for structured data analysis and predictive forecasting.

● Develop and deploy Computer Vision solutions, including object detection,

image segmentation, and feature extraction using architectures like

Transformers (ViT) and CNNs.

● Conduct rigorous model evaluation, hyperparameter tuning, and error analysis to ensure high precision and recall in production environments.

Good-to-Have Skills

MLOps & Infrastructure

● Establish and maintain end-to-end ML pipelines (CI/CD/CT) for automated training, testing,



and deployment using tools like Vertex AI or Kubeflow.

● Implement robust monitoring and logging for agentic workflows to track

"hallucination" rates, latency, and cost efficiency.

● Optimize model inference for scalability and performance, ensuring low-latency responses for real-time applications.

Technical Skills Matrix

Domain Expertise Area Specific Technologies

Agentic AI LLM Orchestration ADK, LangChain,

LangGraph, LlamaIndex

Traditional ML Statistical Modeling Scikit-learn, XGBoost,

LightGBM, Pandas

Deep Learning Frameworks & Vision

PyTorch, TensorFlow,

Keras, HuggingFace,

OpenCV

MLOps(Good-to-Have

Skills) Pipeline & Cloud

Vertex AI, MLflow, Docker,

Kubernetes, Terraform

Data Layers(Positive-to-Have

Skills) Vector & Relational Vector Search, Pinecone,

PostgreSQL, BigQuery

Qualifications

● Experience: Minimum 5+ years of professional experience in AI/ML engineering, with at least 2 years focused on LLM application development or agentic workflows.

● Programming: Expert-level proficiency in Python and experience with asynchronous programming for agentic task execution.

● Systems Design: Proven track record of deploying scalable ML models into production environments.

Recommended Certifications & Learning Paths To excel in this role, candidates are encouraged to complete the following Google

Cloud certifications and Skills Boost labs to demonstrate mastery over modern AI infrastructure:

● Professional Machine Learning Engineer: Official Certification Guide

● ML Infrastructure & Operations: Google Cloud Skills Boost Path

● Advanced Labs & Specializations:

○ Production ML Systems

○ Building Agentic Systems with Vertex AI

○ Generative AI Explorer - Vertex AI

○ MLOps Fundamentals

📌 Senior AI / ML Engineer (Agentic Systems & Core ML) (Gurugram)
🏢 Trigent Software
📍 Gurugram