Application Engineer / Full-Stack Ai Integration Developer

APPLICATION ENGINEER / FULL-STACK AI INTEGRATION DEVELOPER

Experience: 5–7+ Years in software development, including hands-on
full-stack development and practical AI integration. 

ABOUT THE ROLE We are looking for a practical AI Application Engineer
who can identify where AI can solve business problems and integrate AI
capabilities into real web and mobile applications. This is an
application engineering role, not a research scientist role. Strong
software engineering skills are essential, ideally with experience in
the MERN stack.

KEY RESPONSIBILITIES - Work with business stakeholders to understand
workflows and identify suitable AI use cases. - Assess whether a problem
is best solved with conventional code, a third-party service, or an AI
model. - Build AI-powered application features such as chatbots,
document understanding, summarization, classification, information
extraction, and workflow automation. - Integrate LLM APIs such as
OpenAI, Google Gemini, or equivalent providers into web and mobile
applications. - Design prompts, structured outputs, tool/function
calling, context handling, and error/retry strategies. - Where
appropriate, implement retrieval-augmented generation (RAG), embeddings,
and document search. - Evaluate AI outputs for reliability and build
validation, fallback, and human-review mechanisms. - Consider privacy,
access control, prompt injection, hallucinations, latency, and usage
costs. - Use AI development tools to improve coding and testing
productivity while reviewing generated code carefully. - Collaborate
with frontend, backend, mobile, QA, and DevOps teams. - Document AI
workflows, limitations, costs, and expected behavior. - Explain
technical options, risks, and business trade-offs to non-technical
stakeholders.

REQUIRED SKILLS - 5–7+ years of software development experience; strong
production application engineering experience. - Strong
JavaScript/TypeScript and Node.js skills; MERN experience preferred. -
Experience integrating external APIs and designing reliable backend
services. - Hands-on experience with LLM APIs and building AI-enabled
application features. - Understanding of prompt design, structured
outputs, model limitations, and AI response evaluation. - Knowledge of
security, data privacy, testing, logging, and production
troubleshooting. - Strong analytical skills and ability to turn
ambiguous business needs into a practical solution.

GOOD TO HAVE - RAG, embeddings, vector databases, agent/tool workflows,
and document processing. - React Native experience. - Cloud deployment,
Docker, CI/CD, and monitoring. - Experience measuring AI feature
quality, latency, and cost.

IDEAL CANDIDATE Someone who can build useful AI features that work
reliably in production, rather than only demonstrating prompts or
prototypes.