AI Agent Engineer

LLM Orchestration & RAG Development (LangChain/LlamaIndex/PydanticAI Focus)

• Architect complex LangChain pipelines for multi-agent financial workflows
• Build production RAG systems using LlamaIndex for financial document retrieval
• Implement agents with strong type safety and structured outputs
• Design and implement:
• Chain-of-thought reasoning for financial analysis
• Dynamic prompt routing based on query complexity
• Memory management for long-running financial conversations
• Tool integration for agents to access GL, bank feeds, and operational data
• Optimise token usage and response latency for real-time WhatsApp interactions
  
  

• Build high-performance FastAPI services for:
• Agent-to-agent communication protocols
• WhatsApp webhook processing with sub-second response
• Real-time financial data APIs for frontend consumption
• Design GraphQL schemas for flexible financial data queries
• Implement WebSocket connections for live financial updates
• Create robust error handling and retry mechanisms for financial integrations
  
  

• Design and optimise Chroma collections for:
• Financial document embeddings (loan agreements, invoices)
• Conversation history and context retrieval
• Business logic and rule storage
• Implement hybrid search combining vector similarity and metadata filtering
• Build embedding pipelines for various document types (PDFs, emails, chat logs)
  
  

• Deploy and manage LLM applications.
• Implement Redis caching strategies for LLM responses and financial data
• Design microservices architecture for agent deployment
• Set up monitoring and observability for AI pipelines
  
  

• Expert-level proficiency in:
• LangChain: Custom chains, agents, tools, memory systems
• LlamaIndex: Document stores, indices, query engines
• PydanticAI: Agent frameworks, type-safe LLM interactions, structured outputs
• FastAPI: Async programming, dependency injection, middleware
• Strong experience with Python async/await patterns
• Production experience with Chroma or similar vector databases
• Proficiency with Redis for caching and session management
• Experience with data pipeline and storage tools (Kafka, Spark, Airflow) for building scalable systems
  
  

• Knowledge of PostgreSQL and BigQuery for analytical workloadsUnderstanding of financial data structures (journal entries, chart of accounts)
• Experience with financial APIs (QuickBooks, Xero, Plaid, banking APIs)
• Knowledge of data consistency requirements for financial systems
• GraphQL schema design and optimisation
• Experience with WhatsApp Business API
• Background in fintech or accounting software
  
  

• LLMs: GPT-4, Claude, open-source models
• ML/AI: LangChain, LlamaIndex, PydanticAI, PyTorch, Transformers
• Vector DB: Chroma
• Data: PostgreSQL, BigQuery, Apache Kafka, Spark, Airflow
• APIs: FastAPI, GraphQL
• Infrastructure: AWS/GCP, Kubernetes, Docker, Redis
• Monitoring: Prometheus, Grafana, OpenTelemetry
• Work on cutting-edge problems combining LLMs with real-time financial data
• Build systems processing millions of financial transactions
• Direct impact on how thousands of companies manage finances
• Work directly with founders and shape technical direction
  
  

• Building production LangChain and PydanticAI applications at scale
• Creating high-performance APIs that power AI agents
• Designing scalable architectures for financial data processing
• Working with cutting-edge LLM technologies
  
  

• Built production LangChain/LlamaIndex/PydanticAI applications serving 1000+ users
• Created FastAPI services handling high-throughput LLM requests
• Worked with vector databases in production environments
• Designed data processing pipelines for financial or similar domains
• Contributed to open-source AI/ML projects
• Hours: 12:30 PM – 10:00 PM IST
• Location: Ahmedabad office
• Reporting: Direct reporting to Jay Desai
• UK Work Culture: Be part of a collaborative environment inspired by the best of UK work culture.
• 12 Fixed Holidays Per Year: Enjoy a generous holiday package.
• 18 Casual Leaves Per Year: Take time off for personal matters when needed.
• 14 Work from Home Days Per Year: Flexibility to work from home.
• Pantry with Hot Snacks: Enjoy snacks to fuel your day.
• Best in Class Infrastructure: Work in a top-tier office with excellent facilities.
• Dinner Is On Us: We treat the team to a meal!
• Competitive salary based on experience.
• Professional development opportunities, including certifications.
• A dynamic, supportive team environment.