Agentic AI Engineer

Agentic AI Engineer

We are looking for an experienced Senior Agentic AI Engineer to design, develop, and deploy autonomous AI systems that can independently plan, reason, and execute complex business tasks across telecom and fintech domains. The ideal candidate will architect multi-agent systems using appropriate frameworks, integrate AI agents with enterprise APIs and tools, and lead the development of goal-oriented agents capable of making real-time decisions with minimal human intervention. Will also drive technical innovation in autonomous AI solutions while ensuring robust safety mechanisms, scalability, and production reliability for mission-critical business applications.

Key Responsibilities

Agentic AI Development

·       Design and implement autonomous, goal-oriented agents AI agents capable of decision-making, planning, and task execution with minimal human intervention

·       Develop multi-agent systems that can collaborate, negotiate, and coordinate to solve complex business problems.

·       Build AI agents with reasoning capabilities using scalable and robust tools on appropriate agentic AI platforms

·       Build monitoring and debugging tools for non-deterministic agent behaviour/ Guardrai1ls to prevent harmful actions / Comprehensive testing frameworks / Roll back mechanisms / fault-tolerant agentic systems with robust error handling and recovery mechanisms

·       Optimize agent performance for real-time decision making in high-stakes financial and telecom environments

Advanced AI Architecture

·       Architect compound AI systems that combine multiple AI models, tools, and data sources, domain-specific knowledge bases with memory systems and persistent state management; interacting with external APIs and databases

·       Develop multi-modal agents capable of processing text, voice, and structured data

Cross-Functional Partnership

·       Collaborate closely with product managers to translate complex business requirements into agentic AI solutions

·       Partner with domain experts in telecom and fintech to ensure AI agents understand industry-specific workflows and regulations

·       Work with UX/UI teams to design intuitive interfaces for human-agent collaboration

·       Engage with compliance and security teams to ensure agentic systems meet regulatory requirements

Technical Leadership

• Mentor junior engineers and data scientists on ML best practices
• Lead technical discussions and architecture decisions for ML projects
• Collaborate with cross-functional teams including product, engineering, and data t
• Conduct code reviews and establish ML engineering standards
• Present findings and recommendations to technical and non-technical stakeholders

Required Qualifications

Education & Experience

• Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related field
• 8+ years of experience in machine learning, feature engineering, statistical analysis of data, deploying models to prod environment
• 1+ years of solid hands-on experience Agentic AI and deployment

Technical Skills

• Programming Languages
  : Proficiency in Python, with experience in R, Scala, or Java preferred
• ML Frameworks
  : Expert-level experience with TensorFlow, PyTorch, scikit-learn
• Cloud Platforms
  : Experience with AWS, GCP, or Azure ML services
• Big Data Tools
  : Familiarity with Spark, Hadoop, Kafka, or similar distributed systems
• Containerization
  : Experience with Docker, Kubernetes for ML model deployment
• Databases
  : Vector Databases, Proficiency in SQL and experience with NoSQL databases (MongoDB, Cassandra)
• Version Control
  : Git, MLflow, DVC, or similar ML versioning tools

ML Expertise

• Deep understanding of Traditional and Generational ML Models, hyperparameter tuning, feature engineering, EDA, quality measurement, Model convergence, regularization
• Understanding of model interpretability and explainability techniques

Software Engineering

• Strong software engineering principles and design patterns
• Experience with microservices architecture and API development
• Knowledge of software testing, including unit testing for ML code
• Familiarity with monitoring, logging, and debugging distributed systems
• Understanding of security best practices for ML systems

Preferred Qualifications

• Experience with large language models (LLMs) and generative AI
• Knowledge of federated learning, edge AI, or mobile ML deployment
• Experience with real-time inference and low-latency model serving
• Contributions to open-source ML projects or research publications
• Telecommunications domain knowledge and experience with BSS/OSS systems
• Leadership or technical mentoring experience