Available to hire
Hi, I’m Nensi Goswami, an AI/ML Engineer with 5+ years of experience designing and deploying end-to-end AI and Generative AI solutions. I specialize in building document ingestion, RAG pipelines, API development, and agentic workflows to automate knowledge extraction and boost operational efficiency.
I thrive on translating complex data into scalable, secure AI solutions using Python, cloud services (AWS, Azure), and modern MLOps practices. I’m passionate about delivering measurable business impact through reliable models, robust monitoring, and user-friendly dashboards.
Skills
Language
English
Fluent
Work Experience
AI ML Engineer at AT&T
March 1, 2026 - PresentDeveloped an enterprise AI/ML and Generative AI platform leveraging customer usage, billing, and service interaction data to predict churn risk, forecast subscriber and revenue trends, and deliver conversational analytics via Azure OpenAI. Built scalable data pipelines, MLOps workflows, and executive dashboards using Databricks, Spark, MLflow, Power BI, and Azure cloud services. Implemented RAG pipelines using Azure OpenAI, LangChain, and FAISS; developed agentic workflows to automate incident analysis and ticket summarization; processed unstructured documents to support network operations and analytics. Built internal Python APIs to expose AI capabilities to business users and enable interactive front-end applications. Implemented model monitoring and drift detection; evaluated Vertex AI and Azure OpenAI for performance and cost efficiency.
AI ML Engineer at Mind Inventory
July 1, 2022 - January 1, 2026Developed an enterprise Gen AI platform for intelligent document search and conversational knowledge retrieval. Built document ingestion pipelines using AWS Glue and S3; implemented RAG solutions with LangChain, FAISS, OpenAI embeddings; fine-tuned LLaMA-2 and Mistral models using LoRA/PEFT. Deployed secure RAG inference stacks with FastAPI, Lambda, API Gateway, and DynamoDB; designed streaming responses with SSE; implemented multi-stage document chunking and context re-ranking. Built automated evaluation pipelines (RAGAS) and integrated Azure AI Search for secure hybrid search. Designed conversational memory with LangChain and built CI/CD pipelines with GitHub Actions.
Data Science ML Engineer at Inexture Solutions
August 1, 2020 - June 30, 2022Developed a machine learning analytics platform for credit risk, fraud detection, and portfolio monitoring. Built scalable data pipelines using Python, SQL, PySpark, AWS Glue, and Airflow to process transactional data and support predictive analytics. Developed ML models (XGBoost, scikit-learn) for risk and fraud detection; built forecasting models using ARIMA and Prophet. Engineered features, improved data quality, implemented model monitoring, and automated reporting. Delivered explainability with SHAP/LIME and built dashboards in Power BI/Tableau. Supported ETL workflows with Azure Data Factory and MLflow for monitoring and retraining.
Education
Bachelor of Engineering at Ahmedabad Institute of Technology
January 1, 2017 - December 31, 2021Qualifications
AWS Certified Machine Learning – Specialty
January 11, 2030 - June 30, 2026Microsoft Azure AI Engineer Associate (AI-102)
January 11, 2030 - June 30, 2026DP-100 Azure Data Scientist
January 11, 2030 - June 30, 2026Google Professional Machine Learning Engineer
January 11, 2030 - June 30, 2026Databricks Generative AI Fundamentals Accreditation
January 11, 2030 - June 30, 2026Deep Learning Specialization – Coursera / DeepLearning.AI
January 11, 2030 - June 30, 2026Industry Experience
Software & Internet, Telecommunications, Professional Services
Skills
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