Full Stack Developer

Role: Full-Stack Developer (Python + React + Agentic AI)

Experience: 2-6 years

You will build complete AI-powered applications—from frontend screens to backend services, agents, LangGraph pipelines, knowledge graph reasoning, and cloud deployment on AWS and Azure.

Key Responsibilities1. Full-Stack Development (Mandatory)

• Build production-grade applications using FastAPI/Flask and React/Next.js.
• Create enterprise dashboards, workflows, secure login systems (RBAC), and multi-screen interfaces.
• Develop modular UI components for complex AI tasks (generated insights, workflows, exports, reviews).

2. Agentic AI Integration (Mandatory)

• Work with multi-agent frameworks such as LangGraph, CrewAI, or custom orchestrators.
• Implement LLM tools, memory systems, evaluator agents, and deterministic workflows.
• Build RAG pipelines, embeddings, vector search, and tool-based agent orchestration.

3. Knowledge Graph + Ontology Engineering (Mandatory)

Hands-on experience required in at least two of the following:

• Graph databases: Neo4j, Azure Cosmos DB (Gremlin), AWS Neptune
• Ontology design (OWL/JSON-LD), schema creation, triples, relationships
• Creating graph-based reasoning flows (GraphRAG, entity grounding, relationship inference)
• Integrating knowledge graphs with LLMs for retrieval + reasoning
• Designing semantic layers / metric definitions linked to graph schemas

This is a mandatory capability, as all Humigent systems rely on ontology-driven reasoning.

4. Backend Engineering & APIs (Mandatory)

• Build secure microservices and APIs in Python (FastAPI/Flask).
• Strong SQL (PostgreSQL/MySQL), indexing, query tuning.
• Implement PDF/document/Excel ingestion pipelines.
• Build async flows, background tasks (Celery/Redis/RabbitMQ).

5. Cloud Engineering – AWS + Azure (Mandatory)

You must be comfortable deploying and managing workloads on both platforms.

AWS (Mandatory)

• EC2, ECS/EKS, Lambda
• API Gateway, S3, RDS, DynamoDB
• IAM, VPC, Secrets Manager
• CloudWatch, CloudFormation/Terraform preferred

Azure (Mandatory)

• Azure App Service, Azure Functions
• Azure OpenAI
• Azure Blob Storage, Azure SQL/PostgreSQL
• Virtual Machines, VNet, Key Vault
• Azure Monitor, Workbooks, Pipelines

DevOps (Mandatory)

• Docker, GitHub Actions
• CI/CD pipelines
• Secure secrets, environment strategy, logging & monitoring

6. AI/ML & Data Engineering Skills

• Integrate OpenAI, Azure OpenAI, Amazon Bedrock LLMs.
• Use vector DBs: Pinecone, Chroma, Qdrant, Weaviate.
• Familiarity with embeddings, token optimization, semantic caching.
• ETL skills for structured/unstructured data (PDF, tables, Excel, APIs).

Required Skills (Mandatory)Strong Hands-On

• Python + FastAPI/Flask
• JavaScript/TypeScript + React/Next.js
• Agentic AI (LangGraph/CrewAI)
• Knowledge Graphs + Ontology Engineering
• Vector DB + RAG implementation
• AWS + Azure cloud deployments
• SQL (PostgreSQL preferred)
• Docker, CI/CD, GitHub
• Clean code, modular architecture, scalability

Soft Skills

• Ownership mindset
• Strong analytical thinking
• Product-first approach
• Ability to learn quickly
• Collaboration & communication skills
• Passion for AI + problem solving

Nice-to-Have (Bonus)

• Experience with pharma or food-tech datasets (TRx/NRx, FSSAI ingredients)
• Domain experience with clinical data or FDA PDFs
• Experience with cognitive science-based modeling
• GraphRAG, Knowledge Graph visualization, Ontologies like OBI/SNOMED
• Data visualization frameworks (Plotly, ECharts, D3.js)
• Working on high-scale SaaS enterprise applications

Job Type: Full-time

Pay: ₹388,525.00 - ₹1,627,207.67 per year

Work Location: In person