Lead Software Engineer

Staffington Global; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Staffington Global is seeking an experienced Lead Software Engineer passionate about Generative AI and agentic systems. You will design, build, and deploy production-grade AI-powered applications and agent frameworks that transform data interaction and automation.

You will collaborate with ML engineers, data scientists, product managers, and cloud architects to deliver scalable GenAI-based solutions on cloud platforms.

Qualifications

• B.Tech/B.E or ME/M.Tech required; no MCA/M.Sc.
• 8–12 years of software engineering experience.
• Strong backend development with Python and FastAPI.

Responsibilities

• Design and develop GenAI workflows and agentic AI systems.
• Build and deploy high-performance RESTful APIs and asynchronous microservices using FastAPI.
• Deploy AI workloads on AWS (SageMaker, Lambda, API Gateway, Bedrock, S3, ECS/EKS).
• Use Databricks for data processing and MLflow for model tracking.
• Collaborate with ML Engineers, Data Scientists, Product Managers, and Cloud Architects to deliver scalable AI-powered solutions.
• Implement CI/CD and IaC with Terraform, AWS CDK, or similar.

Skills

Python

FastAPI

GenAI

Agentic AI

LLM

RAG

AWS

Databricks

REST APIs

Asynchronous microservices

Cloud-native

Education

B.Tech/B.E or ME/M.Tech

Tools

LangChain

LangGraph

AutoGen

CrewAI

OpenAI

Anthropic

LLaMA

Mistral

SageMaker

Lambda

API Gateway

Bedrock

S3

ECS/EKS

Terraform

AWS CDK

Databricks

MLflow

Job description

Primary Skills: Python, FastAPI, GenAI, Agentic AI, LLM, RAG, AWS, Databricks

Required Qualification: B.Tech/B. E or ME/M.Tech (No MCA; M.Sc) - Preferrably CSC, IT, ECE, AI, EEE

About the Role

We are looking for an experienced Lead 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.

Key Responsibilities

1. 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.
• Build high-performance, scalable RESTful APIs and asynchronous 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.
• 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.
• 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 technologies.

Required Technical Skills

• Strong hands-on experience in Python and backend development.
• Expertise in FastAPI, REST APIs, and asynchronous microservices.
• Hands-on experience with Generative AI, LLMs, and Agentic AI.
• Experience with frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.
• Strong understanding of RAG, vector databases/stores, and semantic search.
• Experience integrating OpenAI, Anthropic, LLaMA, Mistral, or other foundation models.
• Strong experience with AWS services, particularly SageMaker, Lambda, API Gateway, Bedrock, S3, ECS/EKS.
• Experience with Databricks, MLflow, and AI/ML pipeline orchestration.
• Knowledge of CI/CD, Terraform, AWS CDK, and Infrastructure-as-Code.
• Understanding of event-driven architectures, streaming, API security, monitoring, and logging.

Experience & Expectations

• 8–12 years of overall software engineering experience.
• Strong hands-on backend development experience with Python.
• Experience designing and deploying production-grade GenAI and cloud-native applications.
• Ability to contribute to system architecture, technical decisions, and engineering best practices.
• Experience in technical leadership, code reviews, and mentoring junior engineers.