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The job description asks for Python, FastAPI, GenAI, Agentic AI, LLM, RAG, AWS and Databricks. Make sure your resume shows the ones you have, in the words the job uses: applicant tracking systems look for them.

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This is based in Hyderabad, Telangana.

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Lead Software Engineer

Staffington Global

Hyderabad, Telangana, India

Experience: 8–12 Years

Role: Lead Software Engineer

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.

2. API Development & Backend Engineering

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.

3. 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.

4. 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 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.

Interested candidates can share their updated resumes along with their current CTC, expected CTC, Offer in hand (If Any), notice period, Qualification and current location.

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