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, Lang Graph, CrewAI, or Auto Gen 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, Lang Chain,
Lang Graph, Llama Index
Traditional ML Statistical Modeling Scikit-learn, XGBoost,
LightGBM, Pandas

Deep Learning Frameworks & Vision

PyTorch, Tensor Flow,
Keras, Hugging Face,
OpenCV

MLOps(Valuable-to-Have
Skills) Pipeline & Cloud

Vertex AI, MLflow, Docker,
Kubernetes, Terraform

Data Layers(Good-to-Have
Skills) Vector & Relational Vector Search, Pinecone,
PostgreSQL, Big Query

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) (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India