Generative AI Engineer with 7+ years in GenAI, Automation & Data Engineering
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Assessing your cultural and operational fit
Generative AI Engineer & Senior Automation Engineer with 7+ years of experience building and scaling GenAI pipelines, automation frameworks, ETL solutions, and cloud-native data engineering across telecom, financial, and enterprise domains. Proven delivery across LLM integration, RAG pipelines, LangChain, LlamaIndex, chunking & embedding strategies, vector databases (FAISS, Pinecone, Chroma), API automation, big data processing (PySpark, Databricks, Delta Lake), and multi-cloud platforms (AWS, Azure, GCP). Adept at driving engineering excellence in Agile/DevOps environments with a strong bias toward AI-augmented automation and data-driven decision-making.
Master of Computer Applications
MCA
N/A – June 30, 2019
Bachelor of Computer Applications
BCA
N/A – June 30, 2019
Monocept Consulting
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February 1, 2026 – Present
Gurgaon, Haryana, India
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Collabera Technology
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April 1, 2019 – July 1, 2019
Delhi, Delhi, India
ISTQB Certified Tester Foundation Level (CTFL)
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project experience across telecom, financial, and enterprise domains, coupled with their continuous upskilling in cutting-edge AI technologies, indicates a strong adaptability and growth mindset. Their involvement in mentoring and leading teams suggests a collaborative and supportive cultural fit. The explicit mention of 'AI-augmented automation' and 'data-driven decision-making' aligns with a forward-thinking, technology-centric culture. The candidate's current role as a Generative AI Engineer directly aligns with the target role, demonstrating a clear career trajectory and passion for the field.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentorship, and communication skills through their experience in leading teams, conducting knowledge-sharing sessions, and presenting to senior stakeholders. Their experience in incident triage and root-cause analysis indicates strong problem-solving and collaboration abilities. The candidate's proactive approach to upskilling in GenAI and AI engineering aligns well with a dynamic, innovation-driven operational environment.