App Dev & Support Engineer I

About the job

Job Title – App Dev & Support Engineer I – AI Developer

Level: Level 5 –Individual contributor

Location: Kochi, Bangalore, Visakhapatnam

Must have skills: Generative AI, Intelligent Automation, Conversational AI, or Agentic AI, Large Language Models (LLMs), Python, Model Context Protocol (MCP)/ Agent2Agent (A2A), REST APIs

Good to have skills: .NET Full stack development or Power Platform development or VBA/Office script Macros

Experience: 0- 2 years of experience is required

Educational Qualification: B.Tech/BE/M.Tech/MCA

Job Summary
We are seeking a talented and proactive AI Developer to lead the integration of artificial intelligence and Generative AI capabilities into our existing organizational workflows, applications, and business processes. In this role, you will design, build, and deploy end-to-end AI-powered integrations leveraging Azure OpenAI, modern Large Language Models (LLMs), and Vector Databases. The ideal candidate possesses deep expertise in Python-based development, hands-on experience orchestrating API connections to enterprise applications, and an understanding of modern AI architectures such as Retrieval-Augmented Generation (RAG).

Roles And Responsibilities

- Design end-to-end   AI and Generative AI solution architectures   that address business requirements while meeting enterprise standards for scalability, security, performance, reliability, and maintainability.

- Define appropriate architecture patterns for   Generative AI, Agentic AI, RAG, Machine Learning, intelligent automation, conversational AI, and AI-enabled enterprise applications.

- Collaborate with business and technology stakeholders to evaluate AI use cases, identify suitable technologies, assess technical feasibility, and define implementation roadmaps.

- Translate business requirements, functional requirements, and non-functional requirements into scalable and secure   solution architecture designs, architecture diagrams, integration patterns, and technical specifications.

- Design AI solutions using services and technologies available on   AWS, Microsoft Azure, or Google Cloud Platform, including managed AI/ML, data, integration, compute, security, and observability services.

- Define architectures for   LLM-based applications, including prompt orchestration, Retrieval-Augmented Generation (RAG), vector search, embeddings, model routing, grounding, knowledge bases, AI agents, tool/function calling, and multi-agent architectures.

- Design enterprise integration patterns connecting AI solutions with   APIs, databases, data platforms, SaaS applications, enterprise applications, event-driven systems, and external services.

- Evaluate and recommend appropriate   foundation models, LLMs, embedding models, AI platforms, vector databases, orchestration frameworks, and supporting technologies   based on business, technical, security, cost, and performance requirements.

- Define architecture approaches for   AI security, identity and access management, data privacy, guardrails, content filtering, responsible AI, model governance, and regulatory compliance.

- Ability to conduct   AI use-case discovery, technical feasibility assessments, architecture assessments, technology evaluations, and solution option analysis.

- Ability to create and communicate   high-level architecture, detailed solution architecture, sequence diagrams, data flows, integration diagrams, deployment architectures, and architecture decision records.

- Ability to design appropriate   AI guardrails   addressing areas such as hallucination, prompt injection, data leakage, harmful content, unauthorized tool execution, and inappropriate model responses.

- Ability to define   reference architectures, reusable architecture patterns, technical standards, and architecture governance frameworks   for AI solutions.

- Backend API Development: Build high-performance backend microservices, middleware, and integration endpoints using Python (FastAPI, Flask, etc.).

- Prompt Engineering & Evaluation: Develop, test, and refine structured system prompts, guardrails, and automated evaluation frameworks to ensure high-accuracy responses and mitigate hallucination.

Preferred / Optional Qualifications

- Power Platform Experience: Hands-on experience building low-code solutions, custom connectors, or automated workflows using Microsoft Power Apps and Power Automate .

- Full-Stack / Micro-frontend Development: Practical experience in frontend frameworks (React, Vue, or Angular) or microservice architecture.

- Enterprise Automation: Prior exposure to enterprise business process automation, document intelligence, or ticketing/CRM integrations (e.g., ServiceNow, Salesforce).

- Security & Governance: Familiarity with enterprise data privacy standards, role-based access control (RBAC), and responsible AI practices.