Senior Software Engineer

FactSet Research Systems; Hyderabad; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

FactSet Research Systems is seeking a Senior Software Engineer focused on Generative AI, Agentic systems, and cloud-native API development. You will design, build, and deploy production-grade AI-powered applications that transform how clients interact with data and automation.

You will collaborate with ML engineers, data scientists, product managers, and cloud architects to deliver scalable, reliable GenAI solutions powered by cutting-edge technologies across AWS and Databricks.

Formación

• 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.

Responsabilidades

• Design and develop Agentic AI workflows and multi-agent orchestration.
• Build high-performance RESTful APIs and async microservices with FastAPI.
• Deploy and manage AI workloads on AWS and Databricks infrastructure.
• Write clean, testable Python code and mentor peers.

Conocimientos

Python development

Async programming

GenAI technologies

LLMs / RAG / embeddings

API development

Cloud-native architectures

Code reviews / mentoring

Herramientas

FastAPI

OpenAPI/Swagger

SQLAlchemy

Pydantic

Terraform

AWS services

Databricks

Kubernetes

Descripción del empleo

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.

At FactSet, our values are the foundation of everything we do. They express how we act and operate , serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients' needs and exceeding their expectations.

Your Team's Impact

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. You will collaborate closely with ML Engineers, Data Scientists, Product Managers, and Cloud Architects to deliver scalable, reliable, and innovative solutions powered by cutting-edge GenAI technologies.

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 We're 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 - branching strategies, PR workflows, GitOps
• CI/CD - GitHub Actions, GitLab CI, Jenkins, or similar
• Understanding of distributed systems , event streaming (Kafka or AWS Kinesis)