Engineering AI Systems
With Humans in Mind
I'm an Enterprise Solutions Architect, AI & LLM Engineer, and Independent AI Researcher with a strong applied research orientation, building production-grade intelligent systems where human control, safety, reliability, and trust aren't afterthoughts—they're the foundation.
My Approach
My professional work sits at the intersection of enterprise solutioning and hands-on engineering. I translate business requirements into practical architectures, MVP and POC paths, APIs, data flows, AI/LLM systems and implementation roadmaps, while staying close to the engineering required to take those systems into production.
Alongside industry work, I conduct independent and applied research. My research examines how intelligent systems affect human understanding, agency, decision-making and oversight, particularly in education and other high-impact contexts. I combine technical system development with empirical evaluation, user studies, interaction analysis, quantitative evidence and qualitative reasoning.
Across AI projects, I've worked with RAG, GraphRAG, agentic workflows, natural-language analytics, classical machine learning and evaluation pipelines. I also bring experience across AWS, Azure and GCP, enterprise data platforms and customer-data/MarTech systems. Reliability, evaluation, security, observability, cost and appropriate human oversight are design constraints from the beginning—not additions at the end.
Grounded & Reliable
Designing systems with validation, evaluation, guardrails and graceful fallbacks
Human Oversight
Keeping meaningful human control where decisions, safety or accountability demand it
Evidence & Business Value
Balancing technical capability with measurable evidence, cost and real-world usefulness
Research & Scholarly Work
Alongside my professional engineering work, I maintain an active independent research programme focused on how intelligent systems should interact with, support and remain accountable to people.
My current scholarly work spans Human–AI Interaction, Responsible AI, AI-supported education and assessment, learner agency and ownership, human oversight, explainability, fairness and autonomy in AI-assisted decision-making. I am developing multiple academic manuscripts and scholarly contributions at different stages of research, preparation and submission, including journal-oriented applied research, edited-volume chapters and teaching-focused research.
My work combines conceptual framework development with system design, user studies, interaction-log analysis, quantitative evaluation and qualitative evidence. I am not currently enrolled in a PhD programme, and I am actively looking for PhD opportunities that align with this research direction.
Research Themes
- Human–AI Interaction
- Responsible AI
- Human Oversight & Human-in-the-Loop Systems
- Trust Calibration & Autonomy Boundaries
- Explainable AI & Transparency
- AI-Supported Education & Human-Governed Decision Support
Research Methods
- Research Problem Formulation
- Literature Synthesis & Conceptual Framework Development
- User Studies & Mixed-Method Evaluation
- Interaction-Log & Behavioural Analysis
- Quantitative & Qualitative Evidence
- Applied System Evaluation
Scholarly Work in Progress
- Academic Manuscript Development
- Journal-Oriented Applied Research
- Edited-Volume & Book-Chapter Contributions
- Teaching-Case Research
- Research Framing, Evaluation & Evidence Development
- Work at Different Stages of Preparation & Submission
Who I Am
I believe technology should elevate humanity, not replace what makes us human.
Outside of engineering systems and research, I'm a committed fitness enthusiast who never skips the gym—discipline in one area fuels discipline everywhere. I'm deeply curious about different cultures, enjoy meaningful conversations, and find myself naturally drawn to understanding what drives people emotionally.
Family comes first, always. That grounding shapes how I think about technology: it should serve people, help them grow, and create more space for what truly matters—pursuing passions, connecting with loved ones, and living with purpose.
I carry a quiet conviction that one day AI will handle much more of our work. Even then, we'll still need purpose beyond productivity. My goal is to build systems that help people explore, create and live fully—not systems that make them dependent or idle.
Discipline & Consistency
Never skip the gym, never skip the grind
Cultural Curiosity
Learning from different people and perspectives
Family First
The foundation that grounds everything
Human Connection
Understanding people and building meaningful connections
Tech for Good
Building technology that serves people and creates useful change
Purpose-Driven
Creating space for purpose beyond productivity
Technical, Enterprise & Research Skills
Enterprise Solutioning
- Client Discovery & Stakeholder Workshops
- Business & Technical Requirements
- Solution Blueprints & Reference Architectures
- MVP / POC Definition & Planning
- Technical Bids, RFP / RFI Responses & Demos
- Feasibility, Trade-offs, Cost & Implementation Roadmaps
AI / LLM & Agentic Systems
- OpenAI, Claude, Llama, Groq, Mistral & Ollama
- LangChain, LangGraph, CrewAI & Hugging Face
- RAG, GraphRAG, Semantic Search & Embeddings
- Agentic Workflows, Tool Calling & MCP
- FAISS, Pinecone, ChromaDB & Neo4j
- Routing, State, Memory, Caching & Fallbacks
LLMOps & Evaluation
- RAGAS, LangSmith & Evaluation Harnesses
- LLM / RAG Regression Testing & Agent Tracing
- Retrieval Relevance, Groundedness & Hallucination Evaluation
- Tool Selection, SQL Execution & Structured-Output Validation
- Model Routing, Caching, Fallbacks & Token Budgeting
- Production Monitoring, Reliability & Cost Optimisation
Software Engineering
- Python, JavaScript, TypeScript & SQL
- Flask, FastAPI, Django & Node.js
- React, Next.js & HTML/CSS
- REST APIs, GraphQL & Microservices
- Authentication, Integration & Backend Design
- SOLID, Testing & Performance Engineering
Cloud & DevOps
- AWS: SageMaker, ECS, Fargate, EKS, Lambda, S3 & API Gateway
- Azure: Machine Learning, Functions, Container Apps, AKS & App Service
- GCP: Vertex AI, BigQuery, GKE, Cloud Run & Cloud Functions
- Docker, Kubernetes, Helm & Terraform
- Jenkins, GitHub Actions, AWS CodePipeline, Azure DevOps & Cloud Build
- CloudWatch, Azure Monitor, Google Cloud Monitoring, Prometheus & Grafana
Data & Analytics
- PostgreSQL, MySQL & Oracle
- MongoDB, Cosmos DB, DynamoDB, Bigtable & Redis
- Trino, Snowflake & BigQuery
- SQL, ETL & Feature Engineering
- Event, Session, Transaction & Customer-Data Analysis
- Data Modelling, Integration, Quality & Reconciliation
MarTech & Customer Data
- GA4, Google Tag Manager & Google Ads
- Meta Pixel, Meta CAPI & Server-Side Tracking
- Event Instrumentation & E-commerce Tracking
- Attribution, Campaign Measurement & Conversion Reconciliation
- Audience Segmentation, Activation, Remarketing & Retargeting
- Shopify, Mailchimp, Klaviyo, SEMrush & SEO
Machine Learning & MLOps
- scikit-learn, XGBoost, TensorFlow & Gradient Boosting
- Classification, Regression & Feature Engineering
- MLflow Experiment Tracking & Model Versioning
- Hyperparameter Tuning & Model Evaluation
- Model Monitoring, Drift Detection & Retraining
- Production ML Pipelines & Lifecycle Management
Delivery & Governance
- Technical Lead & Subject Matter Expert Responsibilities
- Jira, Roadmaps, Backlogs & Release Planning
- User Stories & Acceptance Criteria
- Cross-Functional Product, Engineering & Data Delivery
- GDPR-Aligned PII Protection & Auditability
- Responsible Production Governance & Human Oversight
Engineering & Research Journey
Lead Enterprise Solutions Architect
Ingest Labs Inc. / MagicPixel, Kansas
Led enterprise solution architecture and client-facing technical delivery across AWS-based systems, APIs, SDKs, event-driven workflows, data platforms and MarTech. Work included PostgreSQL, MongoDB, Trino, GA4, GTM, Google Ads, Meta CAPI and Thinkr AI—an LLM-powered natural-language analytics capability with agentic, schema-aware query planning and deterministic execution.
Lead AI Solutions Architect
Smartail UK, London
Led AI discovery, technical consulting and architecture for GenAI, RAG, GraphRAG and agentic systems across different AWS, Azure and GCP client environments. Work included SmartAsk, DeepGrade AI and LLM Assistants & Agentic Systems, along with evaluation pipelines, production deployment and cost-aware model routing.
Developer & Digital Lead
Avinci LTD, Leicester
Delivered Shopify and Shopify Liquid development, website optimisation, GA4/GTM analytics, SEO and SEMrush work, email and social-media marketing, Snowflake/reporting workflows and customer/campaign analysis.
Independent AI Researcher
Independent / Applied Research
Conducting independent and applied research across Human–AI Interaction, Responsible AI, AI-supported education and human-governed intelligent systems. Current scholarly activity includes multiple academic manuscripts, edited-volume contributions, teaching-case research and journal-oriented applied research at different stages of development, preparation and submission. The work combines conceptual framework development, system building, user studies, interaction analysis and empirical evaluation.
AI Product Builder
AskVish.com
Independently designs and builds production AI and software products including Medvisor AI, ConnectCircle, ATS Forge, Sheet Insight AI, Ad Craft AI and Records Insight AI—covering AI career tools, data analysis, document intelligence, creative generation, healthcare ML and privacy-first social software.
MSc Dissertation — Medvisor AI
Coventry University, United Kingdom
Designed and implemented a full-stack mental-health prediction system using Python, Django, scikit-learn, Gradient Boosting and MLflow. The system achieved 86.9% prediction accuracy and incorporated clinician-verified reports, editable prediction overrides and inspection controls; all six specialists consulted considered human review mandatory for safety-critical predictions.
Senior Software Engineer
Accenture, Bengaluru
Built production backend, full-stack and ML systems using Python, Flask/Django, Node.js, React, AWS and Azure. Worked across APIs, databases, MLOps, cloud migration, CI/CD and model monitoring, while also serving as Scrum Master for a five-member team. Delivered approximately 25% performance improvement and 17% cost reduction.
BTech — Information Technology
Sri Krishna College of Engineering and Technology, India
Built a strong foundation in computer science, software development and database systems, forming the engineering base for later work across enterprise software, AI/ML, cloud, data and production application development.
Interested in Working Together?
I'm open to Enterprise Solutions Architecture and AI / LLM Architecture & Engineering roles, PhD opportunities, research collaborations and selected collaborative projects.