Posted 3 days ago
App Dev & Support Engineer I
AI Summary
Designs, builds and deploys AI and Generative AI integrations using Azure OpenAI, LLMs and vector databases, orchestrating API connections to enterprise applications and developing Python backend services and prompt evaluation frameworks.
About this role
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-endAI and Generative AI solution architecturesthat address business requirements while meeting enterprise standards for scalability, security, performance, reliability, and maintainability.
- Define appropriate architecture patterns forGenerative 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 securesolution architecture designs, architecture diagrams, integration patterns, and technical specifications.
- Design AI solutions using services and technologies available onAWS, Microsoft Azure, or Google Cloud Platform, including managed AI/ML, data, integration, compute, security, and observability services.
- Define architectures forLLM-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 withAPIs, databases, data platforms, SaaS applications, enterprise applications, event-driven systems, and external services.
- Evaluate and recommend appropriatefoundation models, LLMs, embedding models, AI platforms, vector databases, orchestration frameworks, and supporting technologiesbased on business, technical, security, cost, and performance requirements.
- Define architecture approaches forAI security, identity and access management, data privacy, guardrails, content filtering, responsible AI, model governance, and regulatory compliance.
- Ability to conductAI use-case discovery, technical feasibility assessments, architecture assessments, technology evaluations, and solution option analysis.
- Ability to create and communicatehigh-level architecture, detailed solution architecture, sequence diagrams, data flows, integration diagrams, deployment architectures, and architecture decision records.
- Ability to design appropriateAI guardrailsaddressing areas such as hallucination, prompt injection, data leakage, harmful content, unauthorized tool execution, and inappropriate model responses.
- Ability to definereference architectures, reusable architecture patterns, technical standards, and architecture governance frameworksfor AI solutions.
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Backend API Development: Build high-performance backend microservices, middleware, and integration endpoints using Python (FastAPI, Flask, etc.).
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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.
Skills
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