Interfaces people can use
Responsive web applications, accessible interfaces, reusable components, and clear interaction patterns. Performance and usability are part of the implementation.
Aman Meghrajani · Chicago, IL
Full stack engineering.
Applied AI.
Senior software engineer with 10+ years of experience across web, mobile, and cloud systems. I combine React and TypeScript expertise with backend engineering and practical generative AI.
10+ yearsSoftware engineering
Full stack + AIFrontend, backend, and LLMs
React & Next.jsTypeScriptAPIs & cloudRAG & AI agentsWeb & mobile
01 / Software engineering
What I bring
to an engineering team.
I bring together frontend craft, backend engineering, and cloud delivery. My work starts with understanding the problem and continues through implementation, testing, and deployment.
Systems that fit together
APIs, data models, authentication, and integrations that connect the product to the rest of a business. From real-time features to services with clear boundaries.
Experiences beyond the browser
Cross-platform mobile applications, native integrations, and workflows designed for smaller screens, device capabilities, and intermittent connectivity.
A clear path to production
Cloud infrastructure, repeatable releases, automated checks, and observability. I care about how a system behaves after it ships, as well as how it gets built.
02 / Generative AI
Intelligence, connected
to a real workflow.
My AI focus is the application layer: bringing language models, retrieval, and tools into products that people can understand, evaluate, and control.
01UnderstandIntent & context
→02RetrieveRelevant knowledge
→03ActScoped tools & APIs
→04EvaluateQuality & human review
RAG & semantic search
Grounding answers in useful source material with document ingestion, chunking, embeddings, vector retrieval, and citations.
Agents & tool use
Multi-step workflows with explicit state, tool calling, structured outputs, and human approval where an action needs judgment.
AI-native experiences
Assistants, conversational interfaces, and AI features that fit into an existing task, with clear feedback and useful fallbacks.
Evaluation & observability
Checking retrieval relevance and answer quality, comparing prompts, and understanding latency, cost, and failure cases.
Model & tool connectivity
Connecting model APIs, application data, and external tools. Current focus includes MCP and interoperable tool interfaces.
Boundaries by design
Scoped permissions, careful handling of untrusted content, and reviewable actions. Keeping people in control of consequential steps.
Working toolkit & focus
LLM APIs · LangChain · LangGraph · Vector databases · Prompt engineering · Structured outputs · Retrieval · Agent workflows
03 / How I work
A builder’s mindset.
A product perspective.
I enjoy the space where design, engineering, and real-world constraints meet. The goal is software that is useful today and understandable to the people who maintain it tomorrow.
M.S. Software Engineering
Loyola University Chicago
- 01
Start with the problem
Clarify the user, the constraints, and what success means before choosing a stack.
- 02
Make the complexity manageable
Use clear interfaces, sensible architecture, and small, reviewable changes.
- 03
Build a feedback loop
Test the important behavior, observe what happens, and improve from evidence.
- 04
Communicate throughout
Work closely with product, design, and engineering to keep decisions and tradeoffs clear.
Have something in mind?
Let’s talk about
your engineering team.
Interested in Senior Full Stack Engineer, Senior Frontend Engineer, and AI Application Engineer opportunities. Based in Chicago and open to remote teams.
amanmeghrajani@gmail.com