AI/ML Expert

Job Title: AI/ML Expert or Gen AI Engineer

Location: Hyderabad

Experience: 5 to 8 Years

Job Description:

Key Responsibilities:

• Design and deploy Gen AI solutions (e.g., chatbots, anomaly detectors) to automate incident triage, root cause analysis, and alerting in production environments.
• Integrate AI with existing tools like monitoring systems (e.g., Splunk, Dynatrace, Glass box, Catchpoint), ticketing platforms (e.g., Remedy or ServiceNow), and databases (e.g., Oracle) to improve observability.
• Develop custom AI agents or scripts using LLMs (e.g., Claude, Llama, GPT, etc.,) for natural language querying of logs, metrics, and codebases, accelerating MTTR from hours to minutes.
• Collaborate with production support teams to identify toil-heavy processes, prototype AI fixes, and measure impact via KPIs like resolution time and ticket volume.
• Build and maintain AI pipelines for continuous learning from production incidents, ensuring models improve over time without human retraining.
• Ensure AI solutions comply with security, data privacy, and reliability standards in high-stakes financial or enterprise apps.
• Train and upskill support teams on AI tools, fostering a culture of AI-driven efficiency.

Preferred Skills:

• Proficiency in Gen AI frameworks & Transformers for building RAG (Retrieval-Augmented Generation) systems.
• Programming: Python (advanced), with experience in FastAPI, Streamlit for AI prototypes; SQL for database querying (Oracle preferred).
• Production support expertise: Incident management, log analysis, MTTR optimization in cloud (AWS/Azure) environment.
• AI ops: Model deployment via Docker/Kubernetes, monitoring with Prometheus/Grafana, handling drift and hallucinations.
• Data handling: Vector databases (Pinecone, FAISS), prompt engineering for domain-specific tasks like error prediction.

Desired Skills:

• MLOps tools: MLflow for CI/CD of AI models.
• Observability integration: Custom agents for tools.
• Domain knowledge: Global Banking, SRE practices (e.g., SLOs).
• Soft skills: Cross-functional communication, agile methodologies, experience converting AI in conservative teams.
• Emerging tech: Multimodal AI (e.g., vision for dashboard analysis), fine-tuning open-source models on proprietary incident data

Minimum Qualifications (MustHave) *

• 58 years total experience, including 3–5 years of handson GenAI/automation work.
• Strong Python skills for scripting, API integration, and automation