Job description

Job Purpose	Will be a technical IC who is expert in application development and support using Python, NLP, AI ,Langchain, Langgraph, MCP, Kubernetes, DevOps, Azure open AI frameworks
Duties and Responsibilities	• Design and develop intelligent AI Based application using advanced NLP and LLM techniques to solve real-world business challenges in financial services. • Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data. • Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding. • Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask etc. • Should have knowledge of advance prompting techniques • Implement semantic search and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate). • Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required. • Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy. • Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production • Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation etc. • Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks. • Interact with cross teams to understand system issue and follow-up with respective team to get is fixed asap. • Understand and identify areas of improvement across businesses and participate in solution identification and implementation • Should be able to work as an individual contributor role on new & existing projects • Positive and problem-solving attitude, must work as independent contributor
Key Decisions / Dimensions	• Finalizing the Solution design and technical Architecture • Approach for technologies and tools to be used for application development • Preparing application solution design with technical specification • Creation of code, implementation plan and planning deployment • Development Planning and resource planning • Conduct Code Review / Testing • KPI monitoring
Major Challenges	• Keeping up to date with the latest technology • Keep optimizing the application code for optimal usages of resources and scalability. • Handling Production issues and responsible to communicate to business teams • Conduct systematic Root Cause Analysis • Maintaining the system uptime to 100%
Required Qualifications and Experience	a) Qualifications Graduation in computers / electronics or Post Graduation in Computer Science b) Work Experience Experience of 3 – 8 years • Mandatory Skills (tasks may differ basis the below mentioned skill sets) Must have: Core Technical Skills (Mandatory) • Python & API development & maintenance using python- Advanced proficiency with async/await patterns. Production experience with backend. • Experience with deep learning frameworks such as PyTorch or TensorFlow/Keras for building NLP and classification models. • Experience with LLMs and SLMs (e.g., GPT, Mistral, Phi, LLaMA) and applying them in RAG, prompt engineering, and fine-tuning workflows. • Prompt Engineering, Azure Open API, Langchain, Langgraph, AI Agents - Using AI in business application. Knowledge of developing Agents & tools, using LLM logging frameworks • Experience working with embedding models and semantic vector search. • Comfortable with Docker, Git, and working in a CI/CD-enabled development environment. • Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production Good To have: • Machine Learning • Exposure to cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI, or Bedrock). Database & Performance • Database Design, Connection Pooling, Caching Strategies, Error Handling • Postgresql, MongoDB • Redis, Kafka - Caching strategies and async operations Soft Communication • Technical Communication - Ability to explain complex technical concepts • Problem-Solving - Debugging complex distributed systems • Code Review - Constructive feedback and knowledge sharing • Mentoring - Ability to guide junior developers • Strong bias for action & driving results in a high-performance environment. • Exceptionally high motivational levels and needs to be a self-starter.

Someone shared one job with you. ASAI keeps finding the rest.

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Alerts as often as hourly. Reach new roles while the pile is still small.

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Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.

Alerts as often as hourly. Reach new roles while the pile is still small.

Skill gaps, spelled out. See exactly which requirements you don't meet yet.

Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

Job description

Job Purpose	Will be a technical IC who is expert in application development and support using Python, NLP, AI ,Langchain, Langgraph, MCP, Kubernetes, DevOps, Azure open AI frameworks
Duties and Responsibilities	• Design and develop intelligent AI Based application using advanced NLP and LLM techniques to solve real-world business challenges in financial services. • Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data. • Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding. • Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask etc. • Should have knowledge of advance prompting techniques • Implement semantic search and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate). • Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis where required. • Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy. • Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production • Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation etc. • Develop traditional machine learning models (e.g., regression, decision trees, clustering) for structured data analysis and prediction tasks. • Interact with cross teams to understand system issue and follow-up with respective team to get is fixed asap. • Understand and identify areas of improvement across businesses and participate in solution identification and implementation • Should be able to work as an individual contributor role on new & existing projects • Positive and problem-solving attitude, must work as independent contributor
Key Decisions / Dimensions	• Finalizing the Solution design and technical Architecture • Approach for technologies and tools to be used for application development • Preparing application solution design with technical specification • Creation of code, implementation plan and planning deployment • Development Planning and resource planning • Conduct Code Review / Testing • KPI monitoring
Major Challenges	• Keeping up to date with the latest technology • Keep optimizing the application code for optimal usages of resources and scalability. • Handling Production issues and responsible to communicate to business teams • Conduct systematic Root Cause Analysis • Maintaining the system uptime to 100%
Required Qualifications and Experience	a) Qualifications Graduation in computers / electronics or Post Graduation in Computer Science b) Work Experience Experience of 3 – 8 years • Mandatory Skills (tasks may differ basis the below mentioned skill sets) Must have: Core Technical Skills (Mandatory) • Python & API development & maintenance using python- Advanced proficiency with async/await patterns. Production experience with backend. • Experience with deep learning frameworks such as PyTorch or TensorFlow/Keras for building NLP and classification models. • Experience with LLMs and SLMs (e.g., GPT, Mistral, Phi, LLaMA) and applying them in RAG, prompt engineering, and fine-tuning workflows. • Prompt Engineering, Azure Open API, Langchain, Langgraph, AI Agents - Using AI in business application. Knowledge of developing Agents & tools, using LLM logging frameworks • Experience working with embedding models and semantic vector search. • Comfortable with Docker, Git, and working in a CI/CD-enabled development environment. • Exposure to LLMOps tools for monitoring, evaluation, and versioning of AI models in production Good To have: • Machine Learning • Exposure to cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI, or Bedrock). Database & Performance • Database Design, Connection Pooling, Caching Strategies, Error Handling • Postgresql, MongoDB • Redis, Kafka - Caching strategies and async operations Soft Communication • Technical Communication - Ability to explain complex technical concepts • Problem-Solving - Debugging complex distributed systems • Code Review - Constructive feedback and knowledge sharing • Mentoring - Ability to guide junior developers • Strong bias for action & driving results in a high-performance environment. • Exceptionally high motivational levels and needs to be a self-starter.