Ai ML Engineer

Apexon; Bengaluru; On-site; INR 2,500,000 - 3,800,000; Full time

Job summary

Apexon in Bengaluru, India seeks an experienced AI/ML engineer to build and operationalize AI workflows for exception classification, triage, root-cause analysis and remediation recommendations. You will develop agentic workflows with orchestration, tool calling, state management and human-in-the-loop validation, and integrate AI apps with enterprise APIs and data sources.

You will also build reusable tools, apply RAG retrieval, ensure guardrails and traceability, and deliver robust

Qualifications

• Proficient in Python and SQL for data querying and transformation.
• Experience with GenAI / LLM development and deployment.
• Experience with agentic AI and workflow orchestration concepts.

Responsibilities

• Build AI workflows for exception classification, triage, root-cause analysis and remediation recommendations.
• Develop agentic workflows involving orchestration, tool calling, state management and human-in-the-loop validation.
• Correlate new exceptions with historical issues, business rules and data attributes.
• Build Python and SQL-based services to query, transform and analyze enterprise datasets.
• Integrate AI applications with enterprise APIs, databases and internal data sources.
• Develop reusable tools that AI agents can invoke for retrieval, investigation and workflow execution.
• Apply RAG/context retrieval for regulatory docs and knowledge repositories.
• Implement confidence scoring, validation, guardrails and traceability for AI outcomes.
• Build backend services and APIs using Python/FastAPI.
• Implement testing, logging, observability and production engineering practices.
• Collaborate with onshore AI engineers, architects, business analysts and data engineers.

Skills

Python

SQL & Data Analysis

GenAI / LLM Application Development

Agentic AI / Workflow Orchestration

Job description

Key Responsibilities

• Build AI workflows for exception classification, triage, root-cause analysis, impact assessment and remediation recommendations.
• Develop agentic workflows involving orchestration, tool/function calling, state management and human-in-the-loop validation.
• Correlate new exceptions with historical issues, known root causes, business rules and transaction/data attributes.
• Build Python and SQL-based services to query, transform and analyze structured enterprise datasets.
• Integrate AI applications with enterprise APIs, databases, workflow/ticketing platforms and internal data sources.
• Develop reusable tools and services that AI agents can invoke for retrieval, investigation, analysis and workflow execution.
• Apply RAG/context retrieval where regulatory documents, historical knowledge or issue repositories need to be searched.
• Implement confidence scoring, validation, guardrails and traceability for AI-generated outcomes.
• Build backend services and APIs using Python/FastAPI.
• Implement testing, logging, evaluation, observability, exception handling and production engineering practices.
• Collaborate with onshore AI engineers, architects, business analysts, data engineers and application teams.

Skills -

• Python
• SQL & Data Analysis
• GenAI / LLM Application Development
• Agentic AI / Workflow Orchestration