Duties & Responsibilities

Translate business requirements into scalable and well-documented AI/ML pipelines using Databricks, Azure AI, and Snowflake.

Design and deploy GenAI-powered applications using pretrained models (e.g., GPT-4, LLaMA) for tasks such as text generation, summarization, code synthesis, and personalization.

Build and orchestrate agentic AI workflows using frameworks like LangChain, OpenAI Agents SDK, and Databricks Genie, enabling autonomous task execution and multi-agent collaboration.

Integrate GenAI models into enterprise applications with Human-in-the-Loop (HITL) validation and feedback loops for production readiness.

Conduct model selection, fine-tuning, and evaluation using MLflow, ONNX, and custom batch testing frameworks.

Develop and maintain data pipelines for feature engineering, model training, and inference using DBT, Spark, Airflow, and Azure Data Factory.

Monitor and troubleshoot production deployments, addressing model drift, latency, and data quality issues.

Ensure responsible AI operations through governance, observability, and guardrail management using Unity Catalog, Azure AI Guardrails, and OpenTelemetry.

Basic Qualifications

Bachelor’s degree in Computer Science, AI/ML, or a related quantitative field.

3–5 years of experience in AI/ML engineering, with hands-on exposure to GenAI, LLMs, NLP, and agentic architectures.

Proven experience deploying enterprise-grade AI agents, including pre-launch testing, HITL workflows, and business UAT sign-off.

Familiarity with multi-modal AI (text, image, audio) and unstructured data processing using Databricks Genie, AI Foundry, and AI Search.

Experience working in agile, cross-functional teams and delivering measurable impact through automation and intelligent systems.

Preferred Qualifications

Languages: Python, PySpark, SQL

GenAI & LLM Tools: LangChain, LlamaIndex, Hugging Face Transformers, OpenAI Agents SDK, Gemini, LoRA

Agentic Frameworks: LangGraph, Databricks Genie, Azure AI Agent Orchestration

MLOps/LLMOps/AgentOps: MLflow, ONNX, DVC, Unity Catalog, CI/CD pipelines

Data Engineering: DBT, Spark, Lakehouse, Azure Data Factory, Snowflake

Observability & Governance: OpenTelemetry, Databricks AI Gateway, Azure Guardrails