AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer | LLM/RAG/Agentic Systems | Bringing Production-Grade Architecture to AI
Software Architect | Cloud-Native & AI-Driven Systems | Scalable Solution Designer I build AI systems that go beyond prototypes—production-grade LLM and agentic platforms backed by the distributed systems experience needed to actually run them at scale. My background spans both worlds: designing RAG pipelines, LLM-powered workflow assistants, and PyTorch-based prediction models, while also architecting the cloud-native infrastructure (microservices, Kafka, Kubernetes, observability) that supports them in production. This combination—AI fluency plus systems rigor—is what lets me take AI initiatives from proof-of-concept to reliable, scalable deployment. What I bring: • LLM & Agentic AI: RAG pipelines over PostgreSQL/Redis, LangGraph-based agent workflows, LLM API integration for summarization, prediction, and decision intelligence • AI Governance: Built model risk validation processes (SR 11-7), LLM security controls for prompt injection and data leakage, and audit documentation for regulatory compliance • Architect cloud-native, event-driven microservices with strong modularity and observability • Design LLM/Agentic AI layers over existing systems to enable automation and decision intelligence • Lead API strategy, monolith decomposition, and CI/CD excellence • Apply DDD, SOLID, and pragmatic trade-offs for long-term maintainability • Partner with product and engineering teams to turn complex problems into scalable solutions AI & Intelligent Systems • Built LLM-powered workflow assistants and AI wrappers for backend platforms • Designed RAG pipelines over PostgreSQL/Redis for contextual AI responses • Integrated PyTorch models and LLM APIs for prediction, summarization, and insights Tech Java, Spring Boot, Docker, Kubernetes, PostgreSQL, Redis, Kafka, REST, GraphQL, OpenAPI, PyTorch, LLMs, Vector Search Impact •
Space42
Software Engineer
April 1, 2024 – Present
Citi
Assistant Vice President
September 1, 2021 – March 1, 2024
Mississauga, ON · On-site
Crisil
Lead Analyst
September 1, 2021 – July 1, 2023
Credit Suisse
Technical Lead
June 1, 2020 – August 1, 2021
On-site
Symantec
Technical Lead
August 1, 2018 – May 1, 2020
On-site
Software Engineer
June 1, 2017 – July 1, 2018
On-site
GlobalLogic
Associate Consultant
February 1, 2016 – May 1, 2017
Irving, Texas, United States · On-site
Newgen Software Technologies Limited
Senior Software Engineer
July 1, 2014 – January 1, 2016
Noida, Uttar Pradesh, India · On-site
Specsavers
Software Engineer
September 1, 2011 – July 1, 2014
On-site
JK Technosoft Limited.
Software Engineer Trainee
March 1, 2011 – August 1, 2011
Noida
Symantec
February 1, 2019 – August 1, 2021
Skills: Java · Spring Framework · Spring
Resiliency Orchestration
July 1, 2017 – January 1, 2019
Product is to monitor the Disaster Recovery management strategy, minimizing the human efforts at the time of disasters occur and execute the DR strategy with help of this application. Technologies used are micro services using spring boot and Netflix API, REST API ,Service now, JAVA multi-threading and cloud technologies.
AOTA (Application over the air)
February 1, 2017 – May 1, 2018
This project was to develop the client application , that will be used by vehicles in their HeadUnit as a client application. On the server side, there is a system to upgrade and distribute these apps on Vehicles. Tech stack: Java, microservices using spring boot,netflix APIs, angularJS and AWS.
IMP(Import Management PipeLine)
May 1, 2015 – January 1, 2016
IMP system design is introduced to provide c management and control of Scheduled jobs (ETL,script job) through asynchronous communication and dashboard of job related data. Tech stack: Java8, Spring4(JMS, Batch, Admin) AngularJS, Mybatis
PortfolioManager
January 1, 2015 – April 1, 2015
The PM dashboard will be a dynamic representation chart for the dealership’s customer records based on counts, positive equity and thresholds. It also include a Calendar section, Announcement’s/ Bulletins and a Leads Counts section. This data representation can be configured using the different configuration settings available to the Admin user. The calendar functionality will allow the Admin user to view any of the dealership items such as scheduled phone calls, scheduled appointments, scheduled follow-ups and scheduled service appointment’s, based on the record activity stored for a customer record.
Socrates
December 1, 2013 – July 1, 2014
Socrates is a Retail application of a European optical group to use in optical store to manage the customer journey flow. It has multiple module mainly ‘Registration’,’TestRoom’,’Dispense’,’Healthcare’,’Maintenance’. In registration module customer information is registered/updated . In Testroom, customer’s sight test description is being recorded, validating the all sight test rules set by the optician. Dispense Module is being used to create and take the order from customer’s frame and lenses proceeding with payment. Here customer can opt for the discount via insurance,vouchers.Healthcare module is to validate the customer’s health insuarance scheme via webservice exposed by a 3rd party application
CVMS & CMS
September 1, 2011 – December 1, 2013
CVMS (Corporate Voucher Management System) and CMS ( Claim Management System ) Has two module project. CVMS system is used for managing the corporate vouchers for internal and external customers. It has the flow of generating the vouchers order received from the customer (Internal/External) through a central database and then received to application. CVMS system generates and keep the records for those vouchers and then it send the data to central system for the voucher status whether it is used/processed/created. CMS system is used for managing the insurance claims applied against the order/service in the retail store of specsavers. It interacts with Vecozo system through a web service for validating the claims and giving the debits for that order from the insurance companies.
Fundamentals of GIS
University of California, Davis
June 25, 2026 – Present
Convolutional Neural Networks in TensorFlow
DeepLearning.AI
June 25, 2026 – Present
Data Engineering for Google Cloud Platform
ROI Training
June 25, 2026 – Present
Machine Learning with Python (V2)
Coursera
June 25, 2026 – Present
Excel to Power BI
Knowledge Accelerators
June 25, 2026 – Present
Machine Learning with Python
IBM
June 25, 2026 – Present
TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
DeepLearning.AI
June 25, 2026 – Present
AI
DeepLearning.AI
June 25, 2026 – Present
Essential Cloud Infrastructure: Core Services
Coursera
June 25, 2026 – Present
Essential Cloud Infrastructure: Foundation
Coursera
June 25, 2026 – Present
Google Cloud Platform Fundamentals: Core Infrastructure
Coursera
June 25, 2026 – Present
Oracle Certified Professional, Java SE 6 Programmer
Oracle
June 25, 2026 – Present
CP100A: Google Cloud Platform Fundamentals
ROI Training
June 25, 2026 – Present
Generative AI and LLMs: Architecture and Data Preparation
IBM
June 25, 2026 – Present
Professional Cloud Architect Certification
June 25, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse project portfolio spanning various industries (finance, automotive, retail, security) and a long tenure across multiple reputable companies (Citi, Credit Suisse, Symantec, Google). This indicates adaptability and exposure to different organizational cultures. The pursuit of numerous certifications in AI/ML and Cloud technologies demonstrates a proactive learning attitude and a desire to stay current, which aligns well with a culture of continuous improvement. However, the primary experience is in Java/Spring backend development, and the transition to a dedicated ML Engineer role would require a significant shift in focus, which might present a cultural challenge if not adequately supported.
Soft Skills & Operational Fit
The candidate's extensive experience in various technical leadership roles suggests strong operational fit, including project management, team coordination, and architectural decision-making. The project descriptions, while brief, imply an ability to manage complex systems and integrate diverse technologies. However, without specific psychometric test results, a detailed assessment of soft skills like logical reasoning, work attitude, stress handling, and team collaboration cannot be provided.