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Senior Backend Engineer
Skills
1 month ago
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Important information
Contract type:
Part time
Location:
India
Work mode:
Remote
Published on:
15 September 2026
What they need
Overview
We are looking for a Senior AI / Backend Engineer to design and build production-grade AI systems focused on Intelligent Document Processing (IDP), OCR, RAG, LLM applications, and AI-powered automation.
You will be responsible for taking AI capabilities beyond experimentation and into reliable production systems. This includes designing document ingestion and extraction pipelines, developing RAG architectures, integrating LLMs, building AI agents, and creating APIs that connect AI services with business applications.
You will work closely with product and software engineering teams to turn complex AI requirements into scalable, secure, and measurable solutions.
Skills
AI
Python
Backend
FastAPI
Django
RAG
LLM
GenAI
OCR
IDP
NLP
Embeddings
VectorDB
pgvector
ChromaDB
LangChain
LlamaIndex
Agents
MCP
PromptEngineering
API
Microservices
PostgreSQL
Redis
Celery
Async
Docker
AWS Azure
CI/CD
Git Security
Evaluation
Monitoring
Textract
DocumentAI
FineTuning K
ubernetesR
esponsibilities
- Design and develop production-grade AI/ML and backend systems using Python and FastAPI/Django.
- Build OCR and Intelligent Document Processing pipelines for extracting structured information from documents.
- Design document ingestion, preprocessing, parsing, chunking, embedding, retrieval, and validation workflows.
- Build and optimize RAG pipelines using vector databases and semantic search.
- Integrate and work with LLMs such as OpenAI, Claude, Llama and other foundation models.
- Develop and evaluate prompting, structured outputs, tool calling and agentic workflows.
- Design AI systems capable of handling complex and variable document formats.
- Implement document-level and field-level validation to improve extraction accuracy.
- Develop REST APIs and microservices for AI and document-processing services.
- Work with PostgreSQL, Redis and vector databases such as pgvector, ChromaDB or similar technologies.
- Develop asynchronous processing pipelines using tools such as Celery, queues or event-driven architectures.
- Implement AI evaluation frameworks covering accuracy, hallucination, retrieval quality and extraction reliability.
- Explore and implement AI agents and MCP-based integrations where appropriate.
- Deploy AI services using Docker and cloud platforms such as AWS or Azure.
- Collaborate with software engineers to integrate AI capabilities into production applications.
- Ensure appropriate security and privacy controls when handling sensitive documents and data.
- Monitor production AI systems and continuously improve performance, accuracy and reliability.
Within the first 6 months, you will have helped establish reliable production AI infrastructure capable of:
Document → OCR → Extraction → Validation → Embeddings → Retrieval → RAG/LLM → Structured Output → Business Application
The focus is not simply on "using AI", but on building accurate, scalable and production-ready AI systems.
Must-Have Skills
- 5+ years of professional software/backend development experience.
- Strong Python development experience.
- Strong experience with FastAPI, Django or similar backend frameworks.
- Hands-on experience building RAG applications.
- Practical experience with LLM APIs and GenAI applications.
- Understanding of embeddings, semantic search and vector databases.
- Experience with OCR, document processing or IDP is highly preferred.
- Strong REST API and microservices experience.
- PostgreSQL and Redis experience.
- Experience with asynchronous processing/background jobs.
- Docker and cloud deployment experience.
- Strong understanding of API security, authentication and authorization.
- Git and CI/CD experience.
Preferred Skills
- Experience with OpenAI, Claude, Llama or similar LLMs.
- LangChain, LlamaIndex or equivalent frameworks.
- pgvector, ChromaDB, Pinecone, Weaviate or similar.
- MCP / agentic AI systems.
- Document AI, Google Cloud Vision, AWS Textract or Azure Document Intelligence.
- LLM fine-tuning, quantization or inference optimization.
- Experience with Kubernetes.
- Experience with regulated data, healthcare, finance or other sensitive-data environments.
- Experience designing AI evaluation and monitoring systems.
Pay: From ₹30,000.00 per month
Benefits:
- Work from home
Work Location: Remote
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