{"id":3810790,"url":"https://alion.io/job/cogniify-full-stack-ai-software-engineer","title":"Full Stack AI Software Engineer","company":{"id":4610,"name":"Cogniify","domain":"cogniify.ai","url":"https://alion.io/company/cogniify","size_band":"51-200","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","Gurgaon, India","Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Asyncio","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"GraphQL","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"MySQL","optional":false},{"name":"Next.js","optional":false},{"name":"Node JS","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pydantic","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"Amazon ECS","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Braintrust","optional":true},{"name":"Cloudflare","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"Promptfoo","optional":true},{"name":"Ragas","optional":true},{"name":"Vercel","optional":true}],"status":"live","first_seen_at":"2026-11-05T14:35:00Z","employer_posted_date":null,"last_verified_at":"2026-11-05T14:35:00Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"As a Mid-Level AI Engineer (Full Stack AI Software Engineer), you will design, build, and deploy end-to-end intelligent web applications and services. In this role, you will own the full feature loop: building intuitive user interfaces, developing scalable backend APIs, and integrating Generative AI capabilities—such as Large Language Model (LLM) APIs, retrieval-augmented generation (RAG) pipelines, and autonomous AI agent workflows. Working with product managers, designers, and fellow engineers, you will transform product roadmaps and customer workflows into reliable, secure, AI-powered applications.\n\nResponsibilities: \nEnd-to-End AI Feature Delivery: Build, ship, and maintain AI-powered features across the entire stack, connecting modern browser interfaces, backend services, and AI runtimes.\nModern Frontend Engineering: Develop responsive, accessible web interfaces (React, Next.js, or TypeScript) featuring real-time capabilities such as streaming LLM responses, chat components, and interactive data visualisations.\nBackend and Agent Integrations: Build robust backend services and microservices that orchestrate LLM workflows, function/tool-calling protocols (e. g., Model Context Protocol / MCP), and agentic pipelines using Python or TypeScript.\nRAG and Data Pipelines: Implement and maintain retrieval systems, vector store embeddings, document processing workflows, and standard relational database schemas (SQL/PostgreSQL).\nSecurity and Guardrails: Implement enterprise-grade authentication and authorisation (OAuth 2.0, JWT, RBAC), safe API boundaries, rate-limiting, and runtime guardrails to prevent prompt injections and data leaks.\nAI Evaluation and Quality: Write automated unit and integration tests while setting up evaluation pipelines to measure LLM output accuracy, latency, token usage, and regression metrics.\nPerformance and Observability: Monitor full-stack application health, implement structured logging and telemetry, and optimise API and inference latency.\n\nRequirements: \nExperience: 3-6 years of hands-on software development experience building production full-stack web applications and backend APIs.\nFrontend Skills: Proficiency in TypeScript, HTML5/CSS3, and modern frontend frameworks (React, Next.js, or equivalent) with experience handling asynchronous states and streaming data.\nBackend Skills: Strong production experience writing typed, asynchronous backend services using Python (FastAPI, Pydantic, asyncio) and/or Node.js / TypeScript.\nApplied AI and LLMs: Practical experience integrating LLM APIs (OpenAI, Anthropic Claude, or cloud providers) into user-facing software using prompt engineering, structured tool/function calling, or agent frameworks (e. g., LangChain, LangGraph, LlamaIndex, MCP).\nDatabases and Data Modelling: Solid proficiency with relational databases (PostgreSQL, MySQL), SQL query design, and working knowledge of vector databases (pgvector, Pinecone, Qdrant) or caching layers (Redis).\nSecurity and Auth: Practical understanding of web application security, REST/GraphQL standards, OAuth 2.0 workflows, and secure token lifecycle management.\nEngineering Best Practices: Track record of writing clean, testable code, participating in peer code reviews, and using Git with automated CI/CD workflows.\n\nPreferred Qualifications: \nHands-on experience implementing or hosting Model Context Protocol (MCP) servers and clients.\nProduction 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