Senior AI Engineer - AI Agent Systems at auxoai

Setup: Hybrid
Location: Bengaluru, Karnataka
Type: Full-time
Level: senior
Posted: Sep 28, 2026

Summary from listing

AuxoAI is hiring a Senior AI Engineer to design and deploy production-grade AI agents and predictive machine learning systems for enterprise workflows. The role combines LLM-based reasoning with classical machine learning, focusing on agent architectures, tool orchestration, decision-making, memory systems, evaluation, and integration with enterprise data systems. Candidates need 3–7 years of production AI or machine learning experience, strong Python and ML engineering skills, and experience with agent frameworks, cloud AI platforms, RAG, and enterprise integrations. The role is hybrid, requiring three days per week in the office in Mumbai, Bangalore, Hyderabad, or Gurgaon, with immediate or two-week joining prioritized.

Required Skills

AI agents
Machine learning
Python
RAG
Tool calling
MLOps
Enterprise systems

Additional Information

Required Previous Experiences: 3–7 years of experience building machine learning or AI systems in production environments
Hands-on experience training, evaluating, and deploying ML models with scikit-learn, XGBoost, or PyTorch, including feature engineering, cross-validation, and production monitoring
Experience building or extensively customising agent frameworks for real-world applications
Experience designing tool-use or function-calling architectures under practical system constraints
Experience with cloud-native AI platforms, preferably GCP Vertex AI and Gemini, including model deployment, endpoint management, and AI pipeline orchestration
Experience integrating AI solutions with enterprise data systems, including ERP APIs, data lakehouses, or industrial data sources
Strong understanding of RAG architectures, vector databases, and retrieval strategies, with the ability to extend beyond retrieval into agentic reasoning and action
Preferred Qualifications: Experience with reinforcement learning techniques such as policy gradients, value estimation, or reward modeling
Experience building multi-agent or collaborative agent systems
Experience designing evaluation frameworks for agent robustness and reliability
Experience optimising LLM inference pipelines for latency, throughput, and cost efficiency
Familiarity with MLOps practices including model versioning, drift monitoring, retraining pipelines, and model registries
Familiarity with distributed task orchestration systems and large-scale AI workflow management
Translation Company Name: AuxoAI