Senior Applied AI / ML Engineer - Agentic Intelligent Automation

We are looking for a Senior Applied AI / ML Engineer to design and build production-grade AI solutions for complex, high-volume transactional and regulated environments. The role combines machine learning, GenAI/LLMs, agentic workflows and strong software/data engineering.

The ideal candidate is a hands-on engineer who can take AI solutions beyond experimentation and build scalable, explainable and auditable production systems.

Key Responsibilities

- Design and develop ML solutions for anomaly detection, classification, prediction and root-cause analysis.
- Build AI capabilities that can explain anomalies, investigate potential causes and recommend corrective actions.
- Develop controlled agentic AI workflows using LLMs, tool calling, APIs and enterprise data sources.
- Build RAG-based solutions using structured and unstructured enterprise data.
- Integrate AI/ML services into existing transactional and data platforms.
- Develop production-grade Python services, APIs and data-processing components.
- Implement appropriate guardrails, confidence scoring, explainability and human-in-the-loop controls.
- Establish ML/LLM evaluation, monitoring, tracing and auditability.
- Work closely with data, platform, product and domain teams to take AI use cases from concept through production.

Essential Skills

- 7-12 years of software/data engineering experience with strong recent experience in Applied AI/ML.
- Advanced Python and strong production software-engineering practices.




- Strong ML knowledge including classification, regression, anomaly detection and gradient-boosting techniques.
- Experience with explainable AI techniques such as SHAP/feature attribution.
- Hands-on experience with LLMs, structured outputs, tool/function calling and prompt engineering.
- Experience building agentic workflows using LangGraph, Semantic Kernel, LlamaIndex or similar frameworks.
- Strong understanding of RAG, embeddings, vector/hybrid search and retrieval evaluation.
- Robust SQL and data engineering skills; experience with APIs and event/streaming architectures such as Kafka.
- Experience deploying AI/ML workloads on AWS or Azure.
- Understanding of MLOps/LLMOps, model monitoring, evaluation, observability and CI/CD.

Highly Desirable

Experience within banking, capital markets, payments, financial crime, risk, reconciliation, regulatory reporting or other regulated transactional environments would be highly beneficial.

What were looking for

This is not a pure data-science or chatbot-development role. We are looking for an engineer who combines ML depth, up-to-date GenAI/agentic capabilities and strong production engineering skills and can build AI systems where accuracy, explainability, security and auditability matter.

Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr Applied AI / ML Engineer - Agentic & Intelligent Automation (Panipat)
🏢 SSD Shared Services
📍 Panipat