Senior Software Engineer
Factset · Hyderabad · onsite · Posted today
Undisclosed5–7 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
Job Summary
What You'll Do
What Were Looking For
Python Frameworks
GenAI Agentic
Cloud - AWS
Databricks
General Engineering
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
We are looking for a Senior Software Engineer who is passionate about Generative AI, Agentic systems, and cloud-native API development. In this role, you will be a key contributor in designing, building, and deploying production-grade AI-powered applications and intelligent agent frameworks that transform the way our products and customers interact with data and automation.
What You'll Do
GenAI Agentic Development
- Design and develop Agentic AI workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI , or similar
- Build and integrate LLM-powered applications using models from OpenAI, Anthropic, Meta (LLaMA), Mistral , or foundation models on cloud platforms
- Implement Retrieval-Augmented Generation (RAG) pipelines, vector stores, and semantic search capabilities
- Develop multi-agent orchestration systems with defined tool use, memory management, and reasoning loops
- Evaluate, fine-tune, and optimize LLM behavior through prompt engineering and chain-of-thought design
API Development Backend Engineering
- Build high-performance, scalable RESTful APIs and async microservices using FastAPI and Python
- Design clean, modular, and well-documented API contracts following OpenAPI/Swagger standards
- Implement authentication, authorization, rate limiting , and security best practices across APIs
- Develop event-driven and streaming architectures to support real-time AI inference pipelines
Cloud Platform Engineering
- Deploy and manage AI workloads on AWS (SageMaker, Lambda, API Gateway, Bedrock, S3, ECS/EKS)
- Utilize Databricks for large-scale data processing, MLflow model tracking, and AI/ML pipeline orchestration
- Build CI/CD pipelines and infrastructure-as-code (IaC) using tools like Terraform, AWS CDK , or similar
- Ensure scalability, observability, and reliability through cloud-native monitoring and logging practices
Engineering Excellence
- Write clean, testable, production-ready Python code following software engineering best practices
- Conduct code reviews and mentor junior engineers on GenAI patterns and best practices
- Contribute to architectural decisions, technical roadmaps , and engineering documentation
- Stay current with the rapidly evolving GenAI ecosystem and champion the adoption of emerging tools
What Were Looking For
- 5-7 years of professional software engineering experience
- Hands-on Python development in production environments
- Experience with GenAI technologies including LLMs, RAG, embeddings, or prompt engineering
- Building and deploying APIs using FastAPI or similar async Python frameworks
- Experience working with AWS cloud services in a production environment
- Hands-on experience with Databricks for data/AI workloads
Python Frameworks
- Expert-level Python (async programming, type hints, Pydantic, dependency injection)
- FastAPI - routing, middleware, background tasks, OpenAPI spec generation
- Experience with SQLAlchemy, Alembic , or async ORMs
- Unit/integration testing with pytest, pytest-asyncio
GenAI Agentic
- Strong understanding of LLM internals , tokenization, context windows, and model behavior
- Experience with LangChain / LangGraph / AutoGen / CrewAI or similar agentic frameworks
- Familiarity with vector databases - Pinecone, Weaviate, pgvector, ChromaDB, or FAISS
- Knowledge of RAG architectures , chunking strategies, and embedding models
- Hands-on experience with OpenAI API, Anthropic Claude API, AWS Bedrock , or Hugging Face models
Cloud - AWS
- AWS Bedrock - LLM model invocation and management
- AWS Lambda, API Gateway, ECS/EKS - serverless and containerized deployments
- S3, DynamoDB, RDS/Aurora - data storage patterns
- IAM, VPC, Secrets Manager - security and access control
- Familiarity with AWS CDK or CloudFormation
Databricks
- Experience with Databricks Workflows, Delta Lake, Unity Catalog
- Familiarity with MLflow for experiment tracking and model registry
- Using Databricks for AI/BI or LLM serving pipelines
General Engineering
- Docker Kubernetes - containerization and orchestration
- Git
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
Aws LambdaAutomationBedrockclaudeCI/CD PipelinesAuroraasync programmingaws kinesisapisCatalystaws bedrockamazon web servicesAws Api GatewayAlembicAzure OpenAIAnalyticsAWS CDKasynciocloudMicrosoft AzureAPI DevelopmentArtificial IntelligenceAnthropic SDK
About Factset
Factset
Norwalk
US
About
FactSet is a global provider of financial data, analytics, and technology solutions for investment professionals. Its platform integrates market data, research, and portfolio management tools to support asset managers, investment banks, and corporate clients in making informed decisions. By combining cutting-edge technology with deep financial expertise, FactSet delivers scalable insights that drive efficiency, transparency, and performance across the capital markets ecosystem.