Stellaspire
Website:
stellaspire.com
Job details:
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.
- Strong 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 we are looking for:
This is not a pure data-science or chatbot-development role. We are looking for an
engineer who combines ML depth, modern GenAI/agentic capabilities and strong
production engineering skills and can build AI systems where accuracy, explainability,
security and auditability matter.
Click on Apply to know more.
