We are seeking a skilled Artificial Intelligence Specialist to join our team. This role involves designing, training, and deploying machine learning models that power autonomous exception resolution, anomaly detection, and explainable insights.
About the Role:
* The successful candidate will work with multiple large language model ecosystems like OpenAI GPT, Anthropic Claude, Google Gemini, and Meta LLaMA.
* You will implement retrieval-augmented generation pipelines, develop prompt engineering techniques, and integrate memory and explainability into agentic workflows.
Key Responsibilities:
* Design and train machine learning models for production.
* Build retrieval-augmented generation pipelines using vector databases and frameworks like LangChain, LangGraph, and MCP.
* Develop prompt engineering and optimization techniques for agentic interactions.
* Collaborate with data engineering teams to maintain data pipelines for machine learning workloads.
* Conduct feature engineering and embeddings generation on structured and unstructured data.
* Implement model monitoring, drift detection, and retraining pipelines.
* Explore emerging architectures and multi-agent orchestration patterns.
* Cross-functionally collaborate with R&D, data science, product, and engineering teams.
* Mentor junior engineers and contribute to best practices in artificial intelligence engineering.
Required Skills:
* Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field.
* 3+ years building and deploying AI systems.
* Strong Python skills and experience with PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers.
* Hands-on experience with large language models including fine-tuning, prompt design, and inference optimization.
* Familiarity with at least two of the following: OpenAI GPT, Anthropic Claude, Google Gemini, Meta LLaMA.
* Knowledge of vector databases, embeddings, and retrieval-augmented generation pipelines.
* Experience working with both structured and unstructured data at scale.
* Understanding of SQL and distributed data frameworks like Spark or Ray.
* Deep knowledge of AI lifecycle: data preparation, training, evaluation, deployment, and monitoring.
Preferred Qualifications:
* Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen).
* Understanding of AI safety, guardrails, and explainability.
* Hands-on experience deploying AI solutions on cloud platforms.
* Familiarity with MLOps practices including CI/CD, monitoring, and observability.
* Background in anomaly detection, fraud/risk modeling, or behavioral analytics.
* Contributions to open-source AI projects or research publications.