What We Offer:

• Night Shift allowance as per process
• Health Insurance
• Tuition Reimbursement
• Work Life Balance Initiatives
• Rewards & Recognition
• Internal movement through IJP

Key Responsibilities:

AI Application Development (Primary Focus)

• Design and build end-to-end AI-powered applications — conversational chatbots, agentic assistants, document intelligence systems, and real-time AI analytics platforms.
• Develop LangGraph-based agentic workflows with multi-step reasoning, tool orchestration, HITL approval gates, and crash-recovery state persistence.
• Build and integrate LLM APIs (AWS Bedrock, OpenAI, Groq, Gemini, Ollama) into production application backends with pluggable provider abstraction.
• Develop real-time AI features using FastAPI and WebSocket streaming, delivering token-by-token LLM responses to end users.
• Build Text-to-SQL engines, automated data visualization pipelines, and AI-driven analytics features within application layers.
• Integrate multimodal AI capabilities — OCR, document parsing, image understanding — into application workflows where required.

RAG & Knowledge Retrieval Systems:

• Build production-grade RAG pipelines integrating vector databases (Weaviate, Pinecone, OpenSearch) with hybrid dense + BM25 retrieval.
• Implement query transformation, reranking (Cohere, CrossEncoder), and LLM-based citation validation within application flows.
• Design multi-tenant document ingestion pipelines with per-user isolation, lifecycle tracking, and scheduled processing.
• Develop knowledge base chatbot applications with multi-turn conversational memory and sliding window context compaction.

Team Leadership & Solution Architecture:

• Lead a small team of 2–3 AI developers, conducting code reviews, architecture walkthroughs, and delivery planning.
• Create solution architecture diagrams covering application, integration, data flow, cloud, and security layers.
• Act as the technical owner for AI application delivery — from requirements to production deployment.
• Translate business requirements and client use cases into AI application designs and implementation roadmaps.

Backend Engineering & Cloud Deployment:

• Build scalable backend services in Python (FastAPI) with async concurrency, task queuing (Celery + Redis), and scheduled processing (APScheduler).
• Implement RBAC systems, multi-tenant data isolation, and API security patterns within AI application architectures.
• Deploy AI applications on AWS (ECS Fargate, Lambda) via CI/CD pipelines with container orchestration and secrets management.
• Apply performance engineering practices: async circuit breakers, retry logic, connection pooling, and memory optimization for production AI workloads.

Responsible AI & Quality :

• Implement AI guardrails, prompt injection prevention, output validation, and content moderation within application pipelines.
• Build PII detection, audit logging, traceability, and explainability features for compliance-sensitive AI applications.
• Write unit and integration tests for AI application components, ensuring reliability of LLM-integrated workflows

Required Skills:

AI Application Development (Core — Must Have)

• LangGraph, LangChain — agentic workflow design, state machines, conditional routing, tool nodes
• LLM API integration — AWS Bedrock (Claude, Llama, Mistral, Titan), OpenAI GPT-4o, Gemini, Groq, Ollama
• Prompt Engineering — structured prompts, output formatting, few-shot design, chain-of-thought reasoning
• RAG pipeline development — document ingestion, chunking, embedding, hybrid retrieval, reranking, generation
• Conversational AI — multi-turn memory, session management, context compaction, streaming responses
• HITL workflow design — approval gates, escalation flows, human override mechanisms

Backend & API Development

• Python — FastAPI, asyncio, REST API design, WebSocket streaming
• Task queuing — Celery, Redis; Scheduling — APScheduler
• Databases — MongoDB, PostgreSQL, SQLite for application data and lifecycle tracking
• Authentication & Authorization — JWT, RBAC, OAuth, multi-tenant pattern